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Paper Citation Record · LEDGER

Qwen Technical Report

As of 13 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 100 inbound Pith citation observations for arXiv:2309.16609.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2309.16609 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z

measured 114 of 114 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 100 of 1421 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:36:19.598472Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved6
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch3

External citation measurements

92
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation c996a6ee-b6c3-4132-a4ad-a13ee1e62be5 · outbound

This paper cites LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale.

Qwen Technical Report LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-05-24T06:34:00.872029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-07-11T11:50:26.030339Z digest=sha256:b37f47a42f786289bc95bc179a5ac543817ff72c599d22f07d41d2fcd0349a84

Observation 1b8a4ab9-9d77-4dea-aeb6-3e00354dae85 · outbound

This paper cites Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers.

Qwen Technical Report Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-24T06:34:00.878502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:f6668248a5602d410ee9a8399e84ab4b51fbccd840665d5d972922ee5cffaa2b

Observation 5e3d0a1d-e69c-4a54-89ff-ddfa71118e3f · outbound

This paper cites Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant.

Qwen Technical Report Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T06:36:02.796578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:b4c9d04c19aef044bdf9b04d0bc4d8e79260240cb49e0dd81f90ed17810ee7c8

Observation 92be0048-dcc7-4010-906c-9c72801e2c51 · outbound

This paper cites doi: 10.18653/v1/n19-1421.

Qwen Technical Report doi: 10.18653/v1/n19-1421

Reference 4

Resolution
verified exact
doi, observed 2026-05-24T06:34:00.866574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:3ff8b35c07acea09acb0b8ed2ad1887a206c2cdf88b58a8cfe8f2ab50a6d7ec2

Observation 973e0814-3801-41a3-ac80-a6e02fad697e · outbound

This paper cites LaMDA: Language Models for Dialog Applications.

Qwen Technical Report LaMDA: Language Models for Dialog Applications

Reference 5

Resolution
metadata mismatch
local_arxiv, observed 2026-05-24T06:34:00.883972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:d102417b248edd4ce87500e96289a6d96a68ee72b46a75461c460fa61ffb5172

Observation c01f93b2-2add-42f4-aa04-36fcba9905a3 · outbound

This paper cites an unresolved cited work.

Qwen Technical Report Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-05-24T06:36:02.793467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:b5ea2795620307e7878d775f4dbc5741374f99aa8d7c5dafa352e798111a815a

Observation 6c34b133-3027-430f-943e-e21eb5d08809 · outbound

This paper cites an unresolved cited work.

Qwen Technical Report Unresolved cited work

Reference 7

Resolution
parse uncertain
raw_fallback, observed 2026-05-24T06:36:02.790263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:6a5fa7952ab36073da479e5e554cd11e6183326085876f6c17019ab1b8bc2f87

Observation 2a57eecb-1a49-48bd-8001-b14572d12415 · outbound

This paper cites an unresolved cited work.

Qwen Technical Report Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-05-24T06:36:02.787150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:7c266a16a01acbb412ac5ef36e27d257e547eba1043d78182b7e5c9cf0fa7254

Observation 6b38cc10-b6b7-4489-a311-aaee656834c2 · outbound

This paper cites an unresolved cited work.

Qwen Technical Report Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-05-24T06:36:02.784079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:5b91de75c39ebf75751382e0e53c6bc39d3d41eccb9637a705bcf7a270e5ef75

Observation 7c30eb18-cbe2-4bde-8b8f-14841fda2195 · outbound

This paper cites an unresolved cited work.

Qwen Technical Report Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-05-24T06:36:02.780741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:a9608acba4711ff966ea711de16e868dea6946830256bf6e6cae4b34be34f80f

Observation 6004d703-3b7a-486e-8e7b-c78c9254d44b · outbound

This paper cites an unresolved cited work.

Qwen Technical Report Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-05-24T06:36:02.774655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:7d1e6e2bda3338b8d56a25f845486e6f3db340fd42210f8ba073e305f5dad335

Observation 0dae0380-6ef3-4f17-a9c0-1c174b756a1f · outbound

This paper cites an unresolved cited work.

Qwen Technical Report Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-05-24T06:34:02.763485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:d2385380365bfe31f7eb38c1ad688ff890ddf7a4a53db2e2683a947db39e137c

Observation f44f704e-e087-4114-97ba-a3fd375fff7a · outbound

This paper cites 对不 起,我们没有甜苹果,只有红色的苹果。.

Qwen Technical Report 对不 起,我们没有甜苹果,只有红色的苹果。

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T06:36:02.777769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:1d782755120a8532e1b6582ab91df0bcb447e1c72226536aaaf114c69fb426a1

Observation 5f76c366-1590-4583-b774-fd565bc41186 · outbound

This paper cites Therefore, 10b + 10b = 60, which gives b = 3 centimeters and a = 5b = 15 centimeters.

Qwen Technical Report Therefore, 10b + 10b = 60, which gives b = 3 centimeters and a = 5b = 15 centimeters

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T06:36:02.800154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T06:31:51.362908Z digest=sha256:7e961b36270f7ca1d55cb9430bd3016eb6a7a173d581f4e46bccddd293a0cc90

Pith citing papers

Observation b50fdf74-8513-4652-9ad6-80dda8a3b2c8 · inbound

A Survey of Large Language Models cites this paper.

A Survey of Large Language Models Qwen Technical Report

Reference 103

Resolution
verified exact
local_arxiv, observed 2026-05-10T22:46:39.920366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T22:46:39.268353Z digest=sha256:48a2196c5804aea92d061354a4db5bdb8c2bf2169b60ba3e353b35f30c5b5172

Observation 6160dabf-b7a7-459c-af2f-54127ad7ca9c · inbound

OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models cites this paper.

OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models Qwen Technical Report

Reference 109

Resolution
verified exact
local_arxiv, observed 2026-05-17T09:55:35.574328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-17T09:55:35.452649Z digest=sha256:36614adb66382ca41f65b65309f3c9b9723a5e29941ef583f3d3747453e4b2f8

Observation 321f158c-3999-42d6-9ae1-acd3c28b258f · inbound

A Survey on Multimodal Large Language Models cites this paper.

A Survey on Multimodal Large Language Models Qwen Technical Report

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-05-16T02:56:42.500499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-16T02:56:41.658658Z digest=sha256:82030072778b12e13060df5956bed12025e6b4fe68a23514cf3248c13cbb618c

Observation 91047f0d-0d17-49b1-84b0-8e650e9f2100 · inbound

MMBench: Is Your Multi-modal Model an All-around Player? cites this paper.

MMBench: Is Your Multi-modal Model an All-around Player? Qwen Technical Report

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-12T17:20:53.735279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-12T17:20:53.687692Z digest=sha256:08954f4f9d3e772a0d2f969f19b31de4d7f65a5f5d512cc23124c22fc3a683d5

Observation 686a88c1-2cb5-4cc3-9743-96b07e7caff0 · inbound

Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models cites this paper.

Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models Qwen Technical Report

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-12T18:57:28.736051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-12T18:57:28.666194Z digest=sha256:a214a55d18e19f383c1adf48a240940fc86a94ed089cb3fdee70e824e28f5548

Observation 4c2c6bca-cde0-49f6-8cb2-146f805e798a · inbound

ShareGPT4V: Improving Large Multi-Modal Models with Better Captions cites this paper.

ShareGPT4V: Improving Large Multi-Modal Models with Better Captions Qwen Technical Report

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-13T17:08:12.770586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T17:08:12.727773Z digest=sha256:989dc3a1bd5b656487de6f3859f965c3a7f7eb4acd937c6f5bdc3b20d8fb1c24

Observation ab5bbbbe-7d0a-4929-898f-18a46a958f6f · inbound

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks cites this paper.

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks Qwen Technical Report

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-13T22:46:09.774846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T22:46:09.693156Z digest=sha256:c0e640fd89887693029f62a922eb5e483e34436daeefd494f261740094fbe50e

Observation 82d99c5d-308c-4bd1-a0fe-aa0fca777196 · inbound

MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices cites this paper.

MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices Qwen Technical Report

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-16T16:35:38.032133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-16T16:35:37.937462Z digest=sha256:3a0e3935ddbfb65434f2b4fa1326f7154ff501fdf7fc96fc5ec9f1eef6a4f678

Observation 248c80d2-62ca-4eab-a263-bdd7bd594d22 · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey Qwen Technical Report

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-24T04:13:52.854135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T04:13:05.328492Z digest=sha256:945b7bd7ab63690ea130648fff5792a530e5172176d5b05141bd2925fafc10ce

Observation fb253ae0-eb36-4fa7-981c-1a570d4a64cf · inbound

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism cites this paper.

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism Qwen Technical Report

Reference 136

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T06:08:06.200348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-11T06:08:05.550346Z digest=sha256:847e84741d49a5fb105ba985b624868b208e2f204d0cf1e355c5e8337da00ea0

Observation 119f1d15-adf0-4480-9f05-91c5aa804348 · inbound

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models cites this paper.

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models Qwen Technical Report

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-16T02:33:30.191935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-16T02:33:30.143907Z digest=sha256:01d45d396a4461e4f932853a2b1427605e8fbe1e84872d710ab1f8ba369f6a68

Observation fec4c7fd-78be-4eca-ac39-949551cf24bd · inbound

CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology cites this paper.

CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology Qwen Technical Report

Reference 69

Resolution
verified exact
local_arxiv, observed 2026-05-24T03:58:51.435088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T03:58:32.556725Z digest=sha256:e4f96753cb968c3454b1b90687c78faae888984e2a7ed8fb83c44ef2869e566f

Observation 8aaf0172-a3c9-4888-bf69-1375dac1b9b0 · inbound

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models cites this paper.

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models Qwen Technical Report

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-24T03:23:49.660696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-24T03:23:18.827351Z digest=sha256:f61c3ee329d08007167d08d46254c990f00323f5154742fcc96ec7d5ba3f0185

Observation 6bf6961b-baf2-4dc7-bb68-eb062984e149 · inbound

MobileVLM V2: Faster and Stronger Baseline for Vision Language Model cites this paper.

MobileVLM V2: Faster and Stronger Baseline for Vision Language Model Qwen Technical Report

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-18T15:27:52.149961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-18T15:27:51.839171Z digest=sha256:d9563b1fc41ffdbf576165a3c2aacf9fd746da35019b56f499cea1f393383eea

Observation dcddaad8-a124-4dc5-9d3b-db6791fd4343 · inbound

Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive cites this paper.

Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive Qwen Technical Report

Reference 100

Resolution
metadata mismatch
local_arxiv, observed 2026-05-17T23:04:44.460136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-17T23:04:44.287660Z digest=sha256:1684e562ab4a4475d26ccc3d93a3ebf9a76b185b267af857408dc08565d47049

Observation eda3eae5-d5b1-44f5-891f-ab80dbc35a7c · inbound

TempCompass: Do Video LLMs Really Understand Videos? cites this paper.

TempCompass: Do Video LLMs Really Understand Videos? Qwen Technical Report

Reference 71

Resolution
verified exact
local_arxiv, observed 2026-05-17T02:46:16.810660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-17T02:46:16.632743Z digest=sha256:a5d49f9dc0fd783ea191c604199edd6bea7fca787dc0f16f7c51b90ac357587c

Observation fae47672-343f-4e26-81e1-3432eac03063 · inbound

Yi: Open Foundation Models by 01.AI cites this paper.

Yi: Open Foundation Models by 01.AI Qwen Technical Report

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-13T05:47:27.811909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T05:47:27.775529Z digest=sha256:5979b184024c741fc96ae69dbd80277a9dfc7fbe5cc1e3b890dd96168e798b32

Observation d760de62-c2a7-4751-adb9-c142ff1dc699 · inbound

InternLM2 Technical Report cites this paper.

InternLM2 Technical Report Qwen Technical Report

Reference 164

Resolution
verified exact
local_arxiv, observed 2026-05-15T11:44:38.151686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-15T11:44:38.066501Z digest=sha256:0aef52a3638c66e45d162f6766690fc03c07da5fb7b49253830d388cc5c18fce

Observation ca6cc4f2-8ade-47ce-ab55-c5d1f426fd67 · inbound

Are We on the Right Way for Evaluating Large Vision-Language Models? cites this paper.

Are We on the Right Way for Evaluating Large Vision-Language Models? Qwen Technical Report

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-05-12T19:41:44.452157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-12T19:41:44.263663Z digest=sha256:957aa2b6c1d14ce6a9695c0583acf7d4b6323e36b107cce5d007b256bf519867

Observation 25d0182a-3990-471d-b2d7-76f5b2b2ccdf · inbound

MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies cites this paper.

MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies Qwen Technical Report

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-13T18:00:53.484831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T18:00:53.389420Z digest=sha256:72a60a4d212da515138db4a68a15deca75e04d3949291f4566c920409156cff2

Observation d3d84067-01f8-40ea-a830-988413575bc7 · inbound

OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments cites this paper.

OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments Qwen Technical Report

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-13T01:19:32.442790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T01:19:32.406859Z digest=sha256:181b42989bd8f1f14adcf57fb7250d1a507253eb9dc39dc4544084638538b72e

Observation 02d0674f-e83d-44c7-8895-4e93e784bc4a · inbound

How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites cites this paper.

How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites Qwen Technical Report

Reference 4

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local_arxiv, observed 2026-05-12T20:58:59.318399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-12T20:58:58.849040Z digest=sha256:3da7287f9e310f232d3f7f9d24b0d7b99f8eec1d950f529ecf7c61180bfc2510

Observation 3fffebcb-2eff-4b36-aba9-228e3738cc8b · inbound

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model cites this paper.

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model Qwen Technical Report

Reference 132

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metadata mismatch
local_arxiv, observed 2026-05-11T05:36:27.152776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-11T05:36:26.207359Z digest=sha256:6571005a52a4936b2bf143eaf4b549b64da3f8b4e9fe345d3e374e097f20c05b

Observation 14195a31-a63e-4845-b56c-6897930ed764 · inbound

A Survey on Large Language Models for Code Generation cites this paper.

A Survey on Large Language Models for Code Generation Qwen Technical Report

Reference 20

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local_arxiv, observed 2026-05-13T20:18:06.414907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T20:18:06.304134Z digest=sha256:b7161284e00aa0bf5f84047295f9b1138bdd690021393574551b0b050a147104

Observation 8ad7b15b-7468-4c6e-87d2-0c0b3c72b908 · inbound

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark cites this paper.

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark Qwen Technical Report

Reference 5

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verified exact
local_arxiv, observed 2026-05-11T15:51:08.512353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-11T15:51:04.674346Z digest=sha256:3f625294c85e69802ccce92918fb49b9968efbd4b8c1f3a131e41f65ea33add0

Observation c03967db-ae3e-499e-a134-d709eae4276c · inbound

MLVU: Benchmarking Multi-task Long Video Understanding cites this paper.

MLVU: Benchmarking Multi-task Long Video Understanding Qwen Technical Report

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-14T19:55:26.516423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-14T19:55:26.333923Z digest=sha256:cd33584297ca2b509f0ddb1f594485f69d941487cc648846f1949011a8e286a7

Observation f61d9e35-d67e-4b9d-903d-61322cb1a97a · inbound

Mixture-of-Agents Enhances Large Language Model Capabilities cites this paper.

Mixture-of-Agents Enhances Large Language Model Capabilities Qwen Technical Report

Reference 1

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verified exact
local_arxiv, observed 2026-05-16T19:29:34.457133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-16T19:29:34.379712Z digest=sha256:8e0b296f9f88d2379b653c7b5e622d1634496feaeb1049eaad3f8cf2e16b4d3a

Observation e69465a9-741a-414a-87f8-f2c93562fa5f · inbound

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation cites this paper.

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation Qwen Technical Report

Reference 2

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verified exact
local_arxiv, observed 2026-05-11T22:09:16.716043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-11T22:09:16.622717Z digest=sha256:8b2a3dc1380773a4ac15042e33a45b854c56c44eca7c83632bf99ad1ce11bcfb

Observation dc775463-ddae-4a2c-bc93-3a28b135a601 · inbound

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing cites this paper.

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing Qwen Technical Report

Reference 88

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verified exact
local_arxiv, observed 2026-05-16T06:58:36.794561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-16T06:58:36.684583Z digest=sha256:8e3074ba5677571849421235181c5dd904f77a751d531262c21a73fc4e207977

Observation 2f0c8fc7-7aac-413a-8e11-525e10487eeb · inbound

OpenVLA: An Open-Source Vision-Language-Action Model cites this paper.

OpenVLA: An Open-Source Vision-Language-Action Model Qwen Technical Report

Reference 37

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verified exact
local_arxiv, observed 2026-05-10T14:46:36.355072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T14:46:35.942338Z digest=sha256:ab8c5f1a19d401b024d96eab0c9518c80e0269c7572a81176c942d98d9899ce0

Observation 8a2baf5b-41c8-4bec-809b-0ea92ac2c369 · inbound

Refusal in Language Models Is Mediated by a Single Direction cites this paper.

Refusal in Language Models Is Mediated by a Single Direction Qwen Technical Report

Reference 115

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verified exact
local_arxiv, observed 2026-05-13T10:47:56.124084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-13T10:47:55.934081Z digest=sha256:bcca24c8e37735f50fe870ba0c3ad9e3c019ff7d9428072b539645b499c31fa1

Observation 5b592275-c4a4-4f91-961f-feeaa24b4578 · inbound

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs cites this paper.

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs Qwen Technical Report

Reference 10

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verified exact
local_arxiv, observed 2026-05-17T00:05:03.691987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-17T00:05:03.547664Z digest=sha256:7281ae02bb556292da6745fe94c91f39d49948d226ffdfad79817d135e1435f0

Observation 8911546b-1d35-42c6-abb5-1068da101f26 · inbound

Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs cites this paper.

Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs Qwen Technical Report

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-18T23:58:29.085943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-18T23:58:29.040819Z digest=sha256:aa36ce5fde2439b99b048c0d1c4b4cc0322c24c1a64b0caeb7514e302cfc3ae7

Observation e924d2f9-84e9-4735-b28d-25d439659125 · inbound

RouteLLM: Learning to Route LLMs with Preference Data cites this paper.

RouteLLM: Learning to Route LLMs with Preference Data Qwen Technical Report

Reference 6

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verified exact
local_arxiv, observed 2026-05-11T23:27:40.488627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-11T23:27:40.397360Z digest=sha256:a7d6f043cf459f3e258177daf1e491ca303afe6a99174e434305640bc9d19649

Observation 167c8876-5138-4363-a85d-788b0cf83bdd · inbound

LiveBench: A Challenging, Contamination-Limited LLM Benchmark cites this paper.

LiveBench: A Challenging, Contamination-Limited LLM Benchmark Qwen Technical Report

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-15T04:48:26.429793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-15T04:48:26.303240Z digest=sha256:baab2cd0bbe57b212abb79f5124daf57cab4cefc2fd7186e8f707355b8a32f61

Observation b68a006c-9eb8-4538-948d-4afe93788c11 · inbound

LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models cites this paper.

LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models Qwen Technical Report

Reference 4

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verified exact
local_arxiv, observed 2026-05-11T06:01:54.066484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-11T06:01:53.730356Z digest=sha256:b7c33ca699b2477a38e9027093c186908592058a5614c568c9577c4a3e2ab40e

Observation dae2ab3e-4c70-4c3b-9b8b-af41307b040c · inbound

Qwen2-Audio Technical Report cites this paper.

Qwen2-Audio Technical Report Qwen Technical Report

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-11T02:14:45.412152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-11T02:14:45.371564Z digest=sha256:ef9fe5314944be78fa114aba8c7a84e82fe041ffb3df05d05a87a8ef4c9a0fe9

Observation 1ba62e44-8bdd-4a16-8822-5d54080f19fa · inbound

Towards Agentic Runtime Healing cites this paper.

Towards Agentic Runtime Healing Qwen Technical Report

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-05-23T22:15:50.077413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-23T22:14:23.865122Z digest=sha256:5f8d03fc3c12201c7a93636f94672f6b8806be0749ab626dd06b4ac31ebe0edc

Observation 05cf8137-b9ab-41b8-9bfe-f42bfba1c56f · inbound

General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model cites this paper.

General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model Qwen Technical Report

Reference 4

Resolution
metadata mismatch
local_arxiv, observed 2026-05-17T20:50:57.867470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-17T20:50:57.814634Z digest=sha256:b566464eb3c7bce9ff02aa17c1bd07021bfe304121af6bd5df6e55d6efd8c6f5

Observation 899e10d2-4277-4c5c-8efb-a159e65415de · inbound

Optimization Hyper-parameter Laws for Large Language Models cites this paper.

Optimization Hyper-parameter Laws for Large Language Models Qwen Technical Report

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-23T20:45:48.840667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-23T20:45:31.427677Z digest=sha256:e5cd086b90762b78d2c2886348e17bd7715139aec0cb5d6609d56afb4b41ecc0

Observation f8650ce2-953d-4d40-8b58-a194e8ede038 · inbound

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning cites this paper.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Qwen Technical Report

Reference 15

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verified exact
local_arxiv, observed 2026-05-23T20:38:24.906276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-23T20:36:55.159302Z digest=sha256:cf3f3adb1b0837e88e696e4b9c07098e09b91a310a42b329c7b40f8942e6df36

Observation 22cde88a-4462-4687-91ad-af1bd5961376 · inbound

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition cites this paper.

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition Qwen Technical Report

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-23T20:43:25.444713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-23T20:40:09.530799Z digest=sha256:82175395b3b61fb78eaf7ba64e979d9707428d5763d2c9f52268e4a8568f7c11

Observation 1c5a3f04-3968-4ec8-a2a0-08fd1572c5a2 · inbound

Qwen2.5-Coder Technical Report cites this paper.

Qwen2.5-Coder Technical Report Qwen Technical Report

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-10T12:33:38.914041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T12:33:38.867604Z digest=sha256:b2e5e5e796eb64ef51e3cb3ac3bdd52a7ceb7245516c23b92e448464abcdf467

Observation ab2e967a-85df-4c65-8049-d3ac44393d3c · inbound

Emu3: Next-Token Prediction is All You Need cites this paper.

Emu3: Next-Token Prediction is All You Need Qwen Technical Report

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-11T10:56:06.631420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-11T10:56:06.418360Z digest=sha256:c33c2faeacab4374ea9160f9cd0eff4015f2023fbb6b95be9b3dd31ced4c865b

Observation e06f6570-92e6-4b4b-88b7-f28a537fbc80 · inbound

SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference cites this paper.

SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference Qwen Technical Report

Reference 69

Resolution
metadata mismatch
local_arxiv, observed 2026-05-15T14:58:32.384055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-15T14:58:32.303101Z digest=sha256:bd3a36dd29aa8716a98abf54a11f4920c0c4656715d28efe8717fc3ec1bc66e9

Observation 2e1ea430-6eef-46d6-aaf1-ca32f8664414 · inbound

Tree-of-Table: Unleashing the Power of LLMs for Enhanced Large-Scale Table Understanding cites this paper.

Tree-of-Table: Unleashing the Power of LLMs for Enhanced Large-Scale Table Understanding Qwen Technical Report

Reference 2020

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no resolver link, observed 2026-08-12T21:34:25.057428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:34:25.057428Z digest=sha256:029c9d5e417036eb022b11de388cfe74d72a1392ee3a6d16e3a8e168b9a88aed

Observation e700f938-6099-49c1-9cc8-9ad87223acd7 · inbound

NavAgent: Multi-scale Urban Street View Fusion For UAV Embodied Vision-and-Language Navigation cites this paper.

NavAgent: Multi-scale Urban Street View Fusion For UAV Embodied Vision-and-Language Navigation Qwen Technical Report

Reference 28

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unresolved
no resolver link, observed 2026-08-12T21:36:19.598472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:36:19.598472Z digest=sha256:af3c32043ee53dec1ecd65cc7b375fe95875155044d7d4829c423ea5f5be260f

Observation 84b0ac47-7e47-4997-8a23-cfa9ffef0375 · inbound

A Comparative Study of Discrete Speech Tokens for Semantic-Related Tasks with Large Language Models cites this paper.

A Comparative Study of Discrete Speech Tokens for Semantic-Related Tasks with Large Language Models Qwen Technical Report

Reference 28

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no resolver link, observed 2026-08-12T21:27:18.825717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:27:18.825717Z digest=sha256:0e283c91a4d21a6394d26bda415bc1fedceb5e22699153783d8f41756a5d0d6c

Observation c04d130c-f253-4649-9684-58a9b403ed0b · inbound

Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers cites this paper.

Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers Qwen Technical Report

Reference 5

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unresolved
no resolver link, observed 2026-08-12T21:29:17.011443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T21:29:17.011443Z digest=sha256:9f70a51718b5c53a5ae592edd9925617d6734c2947b56e7131734180ed666527

Observation 6ccc004e-c4b6-45f4-bff3-dc65295ecab0 · inbound

Refusal in LLMs is an Affine Function cites this paper.

Refusal in LLMs is an Affine Function Qwen Technical Report

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T21:15:47.605180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T21:15:47.605180Z digest=sha256:b8f31da63d72c683a10d2ef790923b814b13cdf133e13ec0b7a746664e6d98d2

Observation 7785b3e6-9271-4fe4-9d84-f635a49dddb6 · inbound

Enhancing Financial Domain Adaptation of Language Models via Model Augmentation cites this paper.

Enhancing Financial Domain Adaptation of Language Models via Model Augmentation Qwen Technical Report

Reference 23

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no resolver link, observed 2026-08-12T20:55:35.714309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:55:35.714309Z digest=sha256:6c9305fba2b81d08ed6308c0f9aab3af3fd2bcee456a0fa4e1191734a08aefb6

Observation a3ea0d3d-1b6b-4e8f-8f99-da211c12b878 · inbound

LLM-based Bi-level Multi-interest Learning Framework for Sequential Recommendation cites this paper.

LLM-based Bi-level Multi-interest Learning Framework for Sequential Recommendation Qwen Technical Report

Reference 2023

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unresolved
no resolver link, observed 2026-08-12T20:45:36.181165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:45:36.181165Z digest=sha256:2a213545b8a400dbe896a6cd08df6c316a9c00c940b6d1b8121cee71d7aaafe4

Observation 563bb0bf-9cd4-443a-9e66-6c70ac8e21ae · inbound

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference cites this paper.

AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference Qwen Technical Report

Reference 8

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unresolved
no resolver link, observed 2026-08-12T20:16:46.539843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:16:46.539843Z digest=sha256:48cf112ee6fb4fb0f7d1949ac8322694709d02ecf140cf431308ba4f9ab58dc8

Observation 6e27ab6e-8d49-4f7e-a5b2-f40d22d73eb7 · inbound

Number it: Temporal Grounding Videos like Flipping Manga cites this paper.

Number it: Temporal Grounding Videos like Flipping Manga Qwen Technical Report

Reference 1

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unresolved
no resolver link, observed 2026-08-12T19:49:43.271932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:49:43.271932Z digest=sha256:d218a33e2e533227b72f3ef554ae7fdc6a5efe82499be4e6dc0a7f87ecfa9c53

Observation fa117da3-8777-4e39-8129-4e083972e139 · inbound

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization cites this paper.

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization Qwen Technical Report

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-16T09:16:17.323497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-16T09:16:17.150383Z digest=sha256:f8ee671711356cf73669b1671d56f41320895af22407023b7357efaea27c6e86

Observation 949da711-5b8f-447e-9877-b157684412bf · inbound

Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts cites this paper.

Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts Qwen Technical Report

Reference 2

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no resolver link, observed 2026-08-12T19:29:56.297231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:29:56.297231Z digest=sha256:9d6b12fc95a76b5c63e8180a65a5b0e0c072bf328d56f8d9dbadc7dd9beb768b

Observation cfa9f07a-7890-476f-8eb5-6397ea8e2609 · inbound

Can Generic LLMs Help Analyze Child-adult Interactions Involving Children with Autism in Clinical Observation? cites this paper.

Can Generic LLMs Help Analyze Child-adult Interactions Involving Children with Autism in Clinical Observation? Qwen Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T19:23:36.717397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:23:36.717397Z digest=sha256:fb99446ddafb59428bebbd3f891dcbdbc51e1555bd2922d78a30547030115081

Observation 49d949da-4101-48f5-88b1-b60044caf604 · inbound

TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models cites this paper.

TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models Qwen Technical Report

Reference 1

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source=pdf_text observed=2026-08-12T19:03:31.904212Z digest=sha256:ea4e8bbee5a251270c403b4f99c422c7e7c739a91a1a7bda8dfa64ff33484a19

Observation 088586a5-4b62-44ae-956a-ce06b3a6715e · inbound

VersaTune: An Efficient Data Composition Framework for Training Multi-Capability LLMs cites this paper.

VersaTune: An Efficient Data Composition Framework for Training Multi-Capability LLMs Qwen Technical Report

Reference 7

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source=arxiv_source observed=2026-08-12T18:51:31.656209Z digest=sha256:f96eb97feb96129c17e29d3e8098786cb359b39e6e1af33320fef3d7d2ff0a99

Observation 4c4b64b6-44a1-4759-b7dd-23dd16ddac3c · inbound

Safe + Safe = Unsafe? Exploring How Safe Images Can Be Exploited to Jailbreak Large Vision-Language Models cites this paper.

Safe + Safe = Unsafe? Exploring How Safe Images Can Be Exploited to Jailbreak Large Vision-Language Models Qwen Technical Report

Reference 8

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source=pdf_text observed=2026-08-12T18:32:11.964701Z digest=sha256:ee05adf49af46624039d28b820ac6d29752cbeace3d5a8f1942aab7c3d2ab629

Observation f0533e8f-eed5-443c-8d8a-849113d62dd1 · inbound

SymDPO: Boosting In-Context Learning of Large Multimodal Models with Symbol Demonstration Direct Preference Optimization cites this paper.

SymDPO: Boosting In-Context Learning of Large Multimodal Models with Symbol Demonstration Direct Preference Optimization Qwen Technical Report

Reference 7

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source=pdf_text observed=2026-08-12T19:07:29.963727Z digest=sha256:35f3e920073aeab8dc3c8346c23784fae634de72df1c5fa3e009287a9aef9cd4

Observation 660777d5-cb9c-4b98-b151-3a197f179d4e · inbound

FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training cites this paper.

FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training Qwen Technical Report

Reference 3

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source=pdf_text observed=2026-08-12T18:38:18.797615Z digest=sha256:af273d5607b5ce7ecc5e110dca1ba1e446592f60fd8ea46ee77a14290ee8a2c5

Observation 17778b05-f84f-4049-9612-3d8913cca0c5 · inbound

DGSNA: Dynamic Generative Scene-based Noise Addition method cites this paper.

DGSNA: Dynamic Generative Scene-based Noise Addition method Qwen Technical Report

Reference 32

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-23T17:43:47.086524Z digest=sha256:b015daea685a6b50981ed26984c10c99c70f6518d7d9781b8a19d1e096b8aa87

Observation 9cc6ee51-893a-42eb-838c-5a37c553a72a · inbound

RedPajama: an Open Dataset for Training Large Language Models cites this paper.

RedPajama: an Open Dataset for Training Large Language Models Qwen Technical Report

Reference 3

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source=pdf_text observed=2026-08-12T17:39:46.754091Z digest=sha256:28cb13863aa9af018dd1ac1d997334fa53eeedb57839799828f9c907d70cd777

Observation e0cb261c-ad8f-41af-b04a-80822a40782a · inbound

SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models cites this paper.

SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models Qwen Technical Report

Reference 4

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source=pdf_text observed=2026-08-12T16:53:29.810279Z digest=sha256:bea9eba98b909c87a220ac16cb940862641e17a0e16d713f6a347bab0e117619

Observation bfba58d3-e373-49e8-9365-d022cf275ee6 · inbound

AIDBench: A benchmark for evaluating the authorship identification capability of large language models cites this paper.

AIDBench: A benchmark for evaluating the authorship identification capability of large language models Qwen Technical Report

Reference 2015

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source=pdf_text observed=2026-08-12T16:44:36.660559Z digest=sha256:e3a73dea7f6dc544dc849b3beae57eb15b0ac4541d85ed98271deeda5711e46c

Observation 4360089c-9b79-4990-b9c4-1e07183ccc93 · inbound

BIPro: Zero-shot Chinese Poem Generation via Block Inverse Prompting Constrained Generation Framework cites this paper.

BIPro: Zero-shot Chinese Poem Generation via Block Inverse Prompting Constrained Generation Framework Qwen Technical Report

Reference 3

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source=arxiv_source observed=2026-08-12T16:45:25.116880Z digest=sha256:8849173622c67b2d3b1082e192347cddc49bda8a137426cb647fa245e6e0c95e

Observation 0dc437e2-651d-42c1-87e5-6ce472e5c9cd · inbound

FASTNav: Fine-tuned Adaptive Small-language-models Trained for Multi-point Robot Navigation cites this paper.

FASTNav: Fine-tuned Adaptive Small-language-models Trained for Multi-point Robot Navigation Qwen Technical Report

Reference 31

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source=pdf_text observed=2026-08-12T16:43:27.925232Z digest=sha256:60c2a5342732fba95390cf3d421ac87c6597b93e7adbcdf9fa6f513e9b1f01b5

Observation 315dc7ec-e5eb-4f92-b4a9-501bac386e64 · inbound

WavChat: A Survey of Spoken Dialogue Models cites this paper.

WavChat: A Survey of Spoken Dialogue Models Qwen Technical Report

Reference 11

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source=pdf_text observed=2026-08-12T20:13:57.012278Z digest=sha256:06252ecd55ad3f71b2682d66187b9b459c8bdf72281cefa166399058dc7605e8

Observation 1cb83942-27e3-42ed-b684-be149ff8299b · inbound

AddrLLM: Address Rewriting via Large Language Model on Nationwide Logistics Data cites this paper.

AddrLLM: Address Rewriting via Large Language Model on Nationwide Logistics Data Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-12T19:09:57.338367Z digest=sha256:87981d2ac2fbdd754f97211d6be85f1492cf30d9424f05ef2db6c666573d1e2c

Observation 30508ccc-e3ba-41ee-a202-96ea9ac6f0d6 · inbound

Multimodal Autoregressive Pre-training of Large Vision Encoders cites this paper.

Multimodal Autoregressive Pre-training of Large Vision Encoders Qwen Technical Report

Reference 5

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source=pdf_text observed=2026-08-12T15:17:22.391871Z digest=sha256:d883f867783d41ddcacd9cdf4f74eee5ae15e1a4082cff58370344c1e2e56dc9

Observation 199db1fe-006d-42b0-9cae-3f91a61953a0 · inbound

Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning cites this paper.

Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning Qwen Technical Report

Reference 1

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source=pdf_text observed=2026-08-12T15:58:03.107270Z digest=sha256:38d2f7e4d83b0e11454f68f00768889feb91d61fd53264df49032b28c99fe92b

Observation 010a7473-fc9e-4e04-957e-d292964a54b4 · inbound

Evaluating and Advancing Multimodal Large Language Models in Perception Ability Lens cites this paper.

Evaluating and Advancing Multimodal Large Language Models in Perception Ability Lens Qwen Technical Report

Reference 5

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source=pdf_text observed=2026-08-12T15:03:23.871962Z digest=sha256:88a52a227af5b66a45c7e48610a9670ed7e502e2c799d6ed5b1e6b3e10aeea3a

Observation 85c7120d-96d8-4c19-b264-b0f7c5a054fc · inbound

VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection cites this paper.

VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-12T14:56:52.489974Z digest=sha256:b91ef03026a3e9e72ef4c09daefffb8c98e469c5f0a4e639372eadfc91efea5e

Observation 733d3135-d48b-4284-a61b-d1ec8c9b7038 · inbound

High-Resolution Image Synthesis via Next-Token Prediction cites this paper.

High-Resolution Image Synthesis via Next-Token Prediction Qwen Technical Report

Reference 5

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source=pdf_text observed=2026-08-12T14:55:41.614007Z digest=sha256:6f065c082b78c387ffc1c9a3a2815c1c3c76980afe9501cfdb27a855d2450d44

Observation 0326bd57-e697-4c4b-bfe5-2104572df3e2 · inbound

freePruner: A Training-free Approach for Large Multimodal Model Acceleration cites this paper.

freePruner: A Training-free Approach for Large Multimodal Model Acceleration Qwen Technical Report

Reference 4

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source=pdf_text observed=2026-08-12T14:22:07.286320Z digest=sha256:8d090a7e764d8591d8728044687425634d3595d17e077726adad4e8457e4580f

Observation 48fe7eb9-c960-4f7f-bc30-4b99cbc274a6 · inbound

Gotta Hear Them All: Towards Sound Source Aware Audio Generation cites this paper.

Gotta Hear Them All: Towards Sound Source Aware Audio Generation Qwen Technical Report

Reference 2

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source=arxiv_source observed=2026-08-12T14:22:11.489827Z digest=sha256:cd355eb3f46bd262c12ced021d6ff16a024d3d0cc96c663d722cb65511ac099c

Observation 8ba58933-ebfb-4b45-b033-fc65a2a9d328 · inbound

Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy cites this paper.

Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy Qwen Technical Report

Reference 6

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source=arxiv_source observed=2026-08-12T14:21:34.673746Z digest=sha256:0dc07a3bd8a583e4bd13adf23df09588a736f9e459bbfd30fb2e071348440d25

Observation 50a12739-a968-4479-b0aa-5a3dadb49b37 · inbound

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models cites this paper.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Qwen Technical Report

Reference 1

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source=arxiv_source observed=2026-08-12T13:42:10.825545Z digest=sha256:2f43e8972adac4f83e13c2f5aa7ecd729aa3efbc328168f726533c4d349829cb

Observation 73631321-dd41-4aa6-816b-d68c03fa258c · inbound

Language Driven Occupancy Prediction cites this paper.

Language Driven Occupancy Prediction Qwen Technical Report

Reference 1

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source=pdf_text observed=2026-08-12T13:40:32.892776Z digest=sha256:ad09f5f63363b4b2f7bfd9dad4cdf63b96bf66f05347792789e9d5df77ded5ed

Observation 7e51096f-f03a-40a8-a11b-2da8c8c5e946 · inbound

BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching cites this paper.

BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching Qwen Technical Report

Reference 6

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source=arxiv_source observed=2026-08-12T13:36:43.883841Z digest=sha256:2fc993464daa436f0cc7f01db8725807c1e9ff93b07428274efeea7a6de3ae23

Observation 286ea39e-a229-4258-861a-65161cdf1422 · inbound

ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domain cites this paper.

ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domain Qwen Technical Report

Reference 5

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source=pdf_text observed=2026-08-12T14:13:29.633261Z digest=sha256:204a450c6db32b71f9c5a501227d682f8483d68cd0eef09361a0d7994ac3f38a

Observation c692dc30-8d04-46fc-bdb9-69b11c94c281 · inbound

AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks cites this paper.

AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks Qwen Technical Report

Reference 1

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source=pdf_text observed=2026-08-12T14:03:26.456495Z digest=sha256:c0060a7d8dd7fe79504c10ce46e21831bec22276da9f0685864a2a5e9eb13b9c

Observation 2525eaa8-3c53-4d23-acfd-602837efd93d · inbound

Imagine and Seek: Improving Composed Image Retrieval with an Imagined Proxy cites this paper.

Imagine and Seek: Improving Composed Image Retrieval with an Imagined Proxy Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-12T14:02:55.711347Z digest=sha256:be221640eec91ee8d0aaa47f8b58622ede0e95dc9eb00de011276b9542764f00

Observation ca70d7e9-d626-46da-8c41-9f4e0aaa9985 · inbound

FREE-Merging: Fourier Transform for Efficient Model Merging cites this paper.

FREE-Merging: Fourier Transform for Efficient Model Merging Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-12T13:08:37.572492Z digest=sha256:c7f9b7d611fb385a2f7f782f357cefef5740953c7cf8d7216dedb8ea0d1c9d89

Observation 50d5eec3-d37d-47cd-b713-ede7188aca75 · inbound

Seq2Time: Sequential Knowledge Transfer for Video LLM Temporal Grounding cites this paper.

Seq2Time: Sequential Knowledge Transfer for Video LLM Temporal Grounding Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-12T12:47:21.185508Z digest=sha256:8be7162e798c1ee0b4128883b105bf1acc13a9ea6cdeaa5a1e8990dbc988c242

Observation 13aed032-967b-4cf8-9710-ade766c5023b · inbound

ReFINE: A Reward-Based Framework for Interpretable and Nuanced Evaluation of Radiology Report Generation cites this paper.

ReFINE: A Reward-Based Framework for Interpretable and Nuanced Evaluation of Radiology Report Generation Qwen Technical Report

Reference 28

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source=pdf_text observed=2026-08-12T12:21:08.654293Z digest=sha256:3270d44a0d614ae6d289c2f5d4fe74dddfb0cfbc03772c1a32fb221ea245df33

Observation 86a9b760-3f92-4f57-8313-cd21749f3f30 · inbound

VersatileMotion: A Unified Framework for Motion Synthesis and Comprehension cites this paper.

VersatileMotion: A Unified Framework for Motion Synthesis and Comprehension Qwen Technical Report

Reference 6

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source=pdf_text observed=2026-08-12T12:17:48.159192Z digest=sha256:a6f6c2551a7fdd33c0e3e8968f959eaef25c45294235f3f4d3b059b2585f0862

Observation f8ec3f64-1f74-4cb7-9b47-e546d401e7da · inbound

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach cites this paper.

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach Qwen Technical Report

Reference 1

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source=pdf_text observed=2026-08-12T12:21:33.815442Z digest=sha256:90d147682d5bc3dfcb362838346a4ddb4470f83f70b12c7064ebcf55f3eee214

Observation 347243c9-61c3-4207-84bf-53694e795f64 · inbound

PEFTGuard: Detecting Backdoor Attacks Against Parameter-Efficient Fine-Tuning cites this paper.

PEFTGuard: Detecting Backdoor Attacks Against Parameter-Efficient Fine-Tuning Qwen Technical Report

Reference 3

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source=pdf_text observed=2026-08-12T12:11:15.458752Z digest=sha256:031d35e03ac7ac694c91633d7a6ae0f6abcac6894c7f4b44c1e205429829bf55

Observation 76a79547-cf46-4bdc-8e1d-ad7a2f534ae8 · inbound

ShowUI: One Vision-Language-Action Model for GUI Visual Agent cites this paper.

ShowUI: One Vision-Language-Action Model for GUI Visual Agent Qwen Technical Report

Reference 4

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source=pdf_text observed=2026-08-12T12:10:40.301795Z digest=sha256:e9045ae2550a2a16d46700fe443d02ad782c64184fe23461d9470237af4fe78d

Observation b39b94d3-7e74-404b-b65e-122b9f7c3a9b · inbound

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem cites this paper.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Qwen Technical Report

Reference 4

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:07:30.098277Z digest=sha256:cb05a5f0546f8a8e0f2e66aea15ab561fdf6870aa2e60a41a7ec8a25734db153

Observation ef091b08-659e-444b-a3ad-8becc7b819e9 · inbound

Efficient Multi-modal Large Language Models via Visual Token Grouping cites this paper.

Efficient Multi-modal Large Language Models via Visual Token Grouping Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-12T12:25:00.310224Z digest=sha256:6ad1e64b2fea41b58b64e9ebbf7cf23b1b0e03a61786ac07cd94d56144b4c2b8

Observation 7ea29251-8ceb-4bc7-9483-24017ad2b1ac · inbound

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient cites this paper.

Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient Qwen Technical Report

Reference 1

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source=pdf_text observed=2026-08-12T12:06:00.821692Z digest=sha256:b939025f26ea2565513c379d761906e684669bc7ec803f466746392d073f8832

Observation ebb4e11c-4f2b-4fb0-8171-5f3d23a204d6 · inbound

NEMO: Can Multimodal LLMs Identify Attribute-Modified Objects? cites this paper.

NEMO: Can Multimodal LLMs Identify Attribute-Modified Objects? Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-12T11:57:29.012130Z digest=sha256:7c4ed4aa83e77642eaa451aab1b8636df8b039bc638a1419cd5057d498a7c84f

Observation d665f9d1-9b41-4059-a264-c30d769fb6fd · inbound

Curriculum Demonstration Selection for In-Context Learning cites this paper.

Curriculum Demonstration Selection for In-Context Learning Qwen Technical Report

Reference 1

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no resolver link, observed 2026-08-12T11:33:52.969529Z

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source=pdf_text observed=2026-08-12T11:33:52.969529Z digest=sha256:35eec342c4cd0870af296f77366b173681d8b2d75b1e6cdf899f62ad5ac4ffc6

Observation b4958e14-cf02-4362-9c34-9388a08366db · inbound

InputSnatch: Stealing Input in LLM Services via Timing Side-Channel Attacks cites this paper.

InputSnatch: Stealing Input in LLM Services via Timing Side-Channel Attacks Qwen Technical Report

Reference 5

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source=pdf_text observed=2026-08-12T11:29:29.268329Z digest=sha256:6d97e8b175e35f1735746243360bd9c6e3dc16c82b1a4fd660ff31a2505c8844

Observation b45a4f56-b556-43db-aefb-e2d4b3c3a0e6 · inbound

ChatRex: Taming Multimodal LLM for Joint Perception and Understanding cites this paper.

ChatRex: Taming Multimodal LLM for Joint Perception and Understanding Qwen Technical Report

Reference 5

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Observation ae1975a4-d696-44bb-b36c-f293feebca46 · inbound

Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models cites this paper.

Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models Qwen Technical Report

Reference 2

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no resolver link, observed 2026-08-12T10:15:24.999300Z

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Observation 37eebf07-ca3b-485a-b77d-290c9b94a130 · inbound

Quantized Delta Weight Is Safety Keeper cites this paper.

Quantized Delta Weight Is Safety Keeper Qwen Technical Report

Reference 2

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no resolver link, observed 2026-08-12T10:08:55.672293Z

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