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Paper Citation Record · LEDGER

SLOT: Sample-specific Language Model Optimization at Test-time

As of 18 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 6 inbound Pith citation observations for arXiv:2505.12392.

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

pith.paper-citation-record.v1
2505.12392 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:38:17.037405Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:07:30.821966Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

42 of 42 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved35
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 986b9a51-ba5a-442c-b056-75302ff2b13e · outbound

This paper cites The Surprising Effectiveness of Test-Time Training for Few-Shot Learning.

SLOT: Sample-specific Language Model Optimization at Test-time The Surprising Effectiveness of Test-Time Training for Few-Shot Learning

Reference 1

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T20:38:16.862667Z digest=sha256:1cd3cafd598c225d2151f6f3b355851aab95d0017e9877c1cb4cc36d562fe89b

Observation 7573b81f-ef2f-46f0-b8d6-928fc77b82b8 · outbound

This paper cites Qwen Technical Report.

SLOT: Sample-specific Language Model Optimization at Test-time Qwen Technical Report

Reference 2

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no resolver link, observed 2026-08-15T20:38:16.868055Z

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source=pdf_text observed=2026-08-15T20:38:16.868055Z digest=sha256:c20d62e64c3988b6030e5e9da5ac9e94ce55caf708785556065b26b9b312f633

Observation 38bd0204-7d45-41d6-a50e-f718c2400647 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

SLOT: Sample-specific Language Model Optimization at Test-time Evaluating Large Language Models Trained on Code

Reference 3

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source=pdf_text observed=2026-08-15T20:38:16.872974Z digest=sha256:18a9a6a57d80fa820cf0cfeb214f5c0ebdb791c95f1ba0edccd46dbda038ba3f

Observation c6cc15dd-cc75-419f-8a0a-0ca998016cba · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

SLOT: Sample-specific Language Model Optimization at Test-time Training Verifiers to Solve Math Word Problems

Reference 4

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no resolver link, observed 2026-08-15T20:38:16.877288Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T20:38:16.877288Z digest=sha256:4616707d6301f4694cdd098ca74148bc851fa044197d0a4bd488c07e62031a73

Observation 73273f8b-7451-4c14-bdc0-6fc91be149bf · outbound

This paper cites Learning How Hard to Think: Input-Adaptive Allocation of LM Computation.

SLOT: Sample-specific Language Model Optimization at Test-time Learning How Hard to Think: Input-Adaptive Allocation of LM Computation

Reference 5

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source=pdf_text observed=2026-08-15T20:38:16.881661Z digest=sha256:9a35b766a3ada92acbe94738e396e233348448d9d75e19dde04ad59d9d7ab562

Observation c3eef4c6-626b-4496-bec7-3d797728c6bc · outbound

This paper cites Test-time training can close the natural distribution shift performance gap in deep learning based compressed sensing.

SLOT: Sample-specific Language Model Optimization at Test-time Test-time training can close the natural distribution shift performance gap in deep learning based compressed sensing

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-15T20:38:17.510693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:38:16.885975Z digest=sha256:575ae623597cf14776a0a59eae67b3482eef691b52ed1d3957eb3ce4364e0b77

Observation c13331ff-6287-4d59-8acc-3f7f42a7a7ec · outbound

This paper cites Test-time training with masked autoencoders.Advances in Neural Information Processing Systems, 35:29374–29385, 2022.

SLOT: Sample-specific Language Model Optimization at Test-time Test-time training with masked autoencoders.Advances in Neural Information Processing Systems, 35:29374–29385, 2022

Reference 7

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source=pdf_text observed=2026-08-15T20:38:16.890188Z digest=sha256:6965c738ae280fb8a5a35da525657522cf12d3fc48d82369bae60bd7909aca0a

Observation de5708aa-45a5-40a7-87d8-b6d6520f7581 · outbound

This paper cites The Llama 3 Herd of Models.

SLOT: Sample-specific Language Model Optimization at Test-time The Llama 3 Herd of Models

Reference 8

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source=pdf_text observed=2026-08-15T20:38:16.894534Z digest=sha256:a25aa18b22f18029085e5f985d78fa8281d7af2d703c7c78fb1ab783a304bdde

Observation d08dbc8e-943e-4908-a970-5bbd07da5d4c · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

SLOT: Sample-specific Language Model Optimization at Test-time DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 9

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source=pdf_text observed=2026-08-15T20:38:16.898650Z digest=sha256:bc2550ae6d8d7bd3fc53277519f92e868c9571118a3f5c15948e4957a8307abc

Observation 04b713be-57c2-414f-bd5c-c2d525023b2a · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

SLOT: Sample-specific Language Model Optimization at Test-time Measuring Mathematical Problem Solving With the MATH Dataset

Reference 10

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source=pdf_text observed=2026-08-15T20:38:16.903127Z digest=sha256:ba9625b66b5e05a39e495025f1ed1d5756d3063d30673f2783d876009086429c

Observation 050b98c3-b7a7-4a8b-bada-11457ac3ce3e · outbound

This paper cites Parameter-efficient transfer learning for nlp.

SLOT: Sample-specific Language Model Optimization at Test-time Parameter-efficient transfer learning for nlp

Reference 11

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source=pdf_text observed=2026-08-15T20:38:16.907495Z digest=sha256:b119c84d809cf841ca946ce1afab38b3ed00d5f1a6c8bfdca85867fe1b7ab36b

Observation 341ac7c5-d098-4b84-b1aa-7a438fe5725d · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022.

SLOT: Sample-specific Language Model Optimization at Test-time Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022

Reference 12

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source=pdf_text observed=2026-08-15T20:38:16.911973Z digest=sha256:aba636293f8df72d05fcde3919b036bf72adace719711d3d9d8d25ce9ce3ebaa

Observation d3980604-bdb2-4681-9c7d-0dc3fdbac35e · outbound

This paper cites C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models.Advances in Neural Information Processing Systems, 36:62991–63010, 2023.

SLOT: Sample-specific Language Model Optimization at Test-time C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models.Advances in Neural Information Processing Systems, 36:62991–63010, 2023

Reference 13

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source=pdf_text observed=2026-08-15T20:38:16.916224Z digest=sha256:14d1cd877892b303d355f3464dd1a86cec5647736f2d847819cf0c2b9c1f0049

Observation e7d67827-d582-48df-b1f9-7d6f4ef54b2c · outbound

This paper cites A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning.

SLOT: Sample-specific Language Model Optimization at Test-time A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning

Reference 14

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source=pdf_text observed=2026-08-15T20:38:16.920727Z digest=sha256:c60a4d280192040d3f3ac8bdf3334195643dc65acf4ddc68911f8b80c2361fc2

Observation fe6deb32-b237-471c-a812-1e017f76f086 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

SLOT: Sample-specific Language Model Optimization at Test-time Gonzalez, Hao Zhang, and Ion Stoica

Reference 15

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raw_fallback, observed 2026-08-15T20:38:17.466594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:38:16.925003Z digest=sha256:3150c90d7222814bc665dfb10fec77a93982ae37b0c772dd53b3b8e131719d93

Observation 52d4ba75-e817-4553-ad86-78f8dd9a3b45 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

SLOT: Sample-specific Language Model Optimization at Test-time The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 16

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no resolver link, observed 2026-08-15T20:38:16.929184Z

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source=pdf_text observed=2026-08-15T20:38:16.929184Z digest=sha256:617c012d873e7e1d7850bf8e123a86f54c90fa4b1c3312ce034932bd2acd8e10

Observation 8a7e0f14-ebde-48ff-be69-7d0b1c2def29 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

SLOT: Sample-specific Language Model Optimization at Test-time Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 17

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source=pdf_text observed=2026-08-15T20:38:16.933344Z digest=sha256:552c0a3d7476046a4642b1f00bd67577e2ebfdf4628dbfac077fcdbcd13b6abd

Observation 02772e5a-6f2f-4b64-95a9-e3ef28d7b969 · outbound

This paper cites A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks.

SLOT: Sample-specific Language Model Optimization at Test-time A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks

Reference 18

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source=pdf_text observed=2026-08-15T20:38:16.937355Z digest=sha256:cde7e69e3a21d22494b5a785089466594371957d22ced96276db4c19cb1ed992

Observation 7ca01e10-82d6-4c5b-bc2c-171388286475 · outbound

This paper cites Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling.

SLOT: Sample-specific Language Model Optimization at Test-time Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling

Reference 19

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source=pdf_text observed=2026-08-15T20:38:16.941819Z digest=sha256:d28d55fd5eb26b9a12147957e917e1151d6109e892f0bf09986bc239c0f9825c

Observation e84261a0-1bfe-46af-906c-ab656e6e042d · outbound

This paper cites P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks.

SLOT: Sample-specific Language Model Optimization at Test-time P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

Reference 20

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no resolver link, observed 2026-08-15T20:38:16.946128Z

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source=pdf_text observed=2026-08-15T20:38:16.946128Z digest=sha256:2ca318e2fe32ab6e013afd6a3c17be6d75d78a15de393a181b144a0ef36d7e6e

Observation feedad1f-a017-45ea-b62b-ffe4e02c4fe2 · outbound

This paper cites Ttt++: When does self-supervised test-time training fail or thrive?Advances in Neural Information Processing Systems, 34:21808–21820, 2021.

SLOT: Sample-specific Language Model Optimization at Test-time Ttt++: When does self-supervised test-time training fail or thrive?Advances in Neural Information Processing Systems, 34:21808–21820, 2021

Reference 21

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source=pdf_text observed=2026-08-15T20:38:16.950336Z digest=sha256:f7c78a24795d0846b1d4451609b2712600d6ded771f1b1d357f1d18c76494874

Observation 3bdb711e-f310-4e16-8474-8d909e164ffe · outbound

This paper cites Decoupled Weight Decay Regularization.

SLOT: Sample-specific Language Model Optimization at Test-time Decoupled Weight Decay Regularization

Reference 22

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source=pdf_text observed=2026-08-15T20:38:16.954211Z digest=sha256:428d1b6c2d81a9067278e49ba7f7f4bcb12c98888dccaa08cb5dfa6db6638496

Observation 33c4cd93-3ea7-403c-8d5c-fc70557544d2 · outbound

This paper cites Language Models are Few-Shot Learners.

SLOT: Sample-specific Language Model Optimization at Test-time Language Models are Few-Shot Learners

Reference 23

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source=pdf_text observed=2026-08-15T20:38:16.958199Z digest=sha256:761c5cf8ab84f2bb2cb17e6b69d4a47f4e00422f1a2a88e32b31e90d7a6feea8

Observation e752f4b3-7b39-4de7-b8c4-3264b7c11ae7 · outbound

This paper cites Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation.

SLOT: Sample-specific Language Model Optimization at Test-time Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation

Reference 24

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source=pdf_text observed=2026-08-15T20:38:16.962058Z digest=sha256:d0e312f8b389937e68d5b87c1e4df12cb8f5abdb16296799a67a75ac9cb24296

Observation c6303c76-ab54-481f-a432-3ae39a21d958 · outbound

This paper cites Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?.

SLOT: Sample-specific Language Model Optimization at Test-time Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Reference 25

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source=pdf_text observed=2026-08-15T20:38:16.965914Z digest=sha256:f5b5fb1660ca4999b0d52781ab984887e6a019b396f4beb02d0cb5871baa445a

Observation 09d81cfd-dc9a-43bd-baa1-17059074609d · outbound

This paper cites Improving Black-box Robustness with In-Context Rewriting.

SLOT: Sample-specific Language Model Optimization at Test-time Improving Black-box Robustness with In-Context Rewriting

Reference 26

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source=pdf_text observed=2026-08-15T20:38:16.970305Z digest=sha256:89b55e793783362a9405e267e175d64ea3849df3e0d963cad70c9c35eb3c08d5

Observation 088ed9d4-eccb-4cf5-b1f0-49a5e60867f7 · outbound

This paper cites Tttflow: Unsupervised test-time training with normalizing flow.

SLOT: Sample-specific Language Model Optimization at Test-time Tttflow: Unsupervised test-time training with normalizing flow

Reference 27

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raw_fallback, observed 2026-08-15T20:38:17.447277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:38:16.974689Z digest=sha256:a50f89aa60b17a6500f63a1808bb1700dd64a9e3ca6e3fbadebc7599d51bcdfe

Observation 4653fa01-6f0f-4a58-89f0-457f52d14f08 · outbound

This paper cites Gpqa: A graduate-level google-proof q&a benchmark.

SLOT: Sample-specific Language Model Optimization at Test-time Gpqa: A graduate-level google-proof q&a benchmark

Reference 28

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source=pdf_text observed=2026-08-15T20:38:16.978638Z digest=sha256:6d90772f4c80ea1cde7b7107460c030d5634660f5c740545a0481e55b3b93e8f

Observation 60f8ee74-291c-4823-9140-bfc16300c2c4 · outbound

This paper cites Towards real-world test-time adaptation: Tri-net self-training with balanced normalization.

SLOT: Sample-specific Language Model Optimization at Test-time Towards real-world test-time adaptation: Tri-net self-training with balanced normalization

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-15T20:38:17.427328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:38:16.982354Z digest=sha256:4fcc262ffe0882c637b4426b8db4edfc5cf50e69806b28dce8f4411607c509fd

Observation 434269cb-6a58-4f86-ae91-c49652ab7c27 · outbound

This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

SLOT: Sample-specific Language Model Optimization at Test-time Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 30

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source=pdf_text observed=2026-08-15T20:38:16.986205Z digest=sha256:6adb447678bbad3ccefae5ea36a9e972f2c6936a2a33338ac722a93c88e3045f

Observation 5dd43cf7-598d-4a59-8e54-d04d7a48a18f · outbound

This paper cites Learning to (Learn at Test Time).

SLOT: Sample-specific Language Model Optimization at Test-time Learning to (Learn at Test Time)

Reference 31

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source=pdf_text observed=2026-08-15T20:38:16.990116Z digest=sha256:9a502db000721fe1e0bef49fa87029830a1310dc59b3c264087560f52f78fbc3

Observation 2985d54d-e242-4666-bfa3-b984451a513b · outbound

This paper cites Test- time training with self-supervision for generalization under distribution shifts.

SLOT: Sample-specific Language Model Optimization at Test-time Test- time training with self-supervision for generalization under distribution shifts

Reference 32

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raw_fallback, observed 2026-08-15T20:38:17.413863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:38:16.994116Z digest=sha256:cd62c41c07ba82334ab4dad4f0bdc1b272b5d4ade411398e97f60bad1e3223f3

Observation 4045d2b4-f3dc-4d6e-a4cf-40acf894e090 · outbound

This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.

SLOT: Sample-specific Language Model Optimization at Test-time Tent: Fully Test-time Adaptation by Entropy Minimization

Reference 33

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source=pdf_text observed=2026-08-15T20:38:16.998243Z digest=sha256:18b6262ac769e7bc04c3af7eaf277173d5d4daa526579609e4acf33dc26897d3

Observation fbf0a411-64df-460b-acae-f9d75d19d280 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

SLOT: Sample-specific Language Model Optimization at Test-time Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 34

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source=pdf_text observed=2026-08-15T20:38:17.002426Z digest=sha256:f664c1782da87bb6a1af2d61eea9ec185ec9cac3a45ed0a557393ab14ac14423

Observation 4407432e-bcf3-4586-93c4-dda52f9fc7bd · outbound

This paper cites Beyond Model Adaptation at Test Time: A Survey.

SLOT: Sample-specific Language Model Optimization at Test-time Beyond Model Adaptation at Test Time: A Survey

Reference 35

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source=pdf_text observed=2026-08-15T20:38:17.006489Z digest=sha256:3f3e2dbb8a5888ba497ced677cf25b34db0063060f35e0579b8b6904834f6887

Observation f7738cbe-275b-4833-83e5-26a53ddc0209 · outbound

This paper cites Stta: enhanced text classification via selective test-time augmentation.PeerJ Computer Science, 9:e1757, 2023.

SLOT: Sample-specific Language Model Optimization at Test-time Stta: enhanced text classification via selective test-time augmentation.PeerJ Computer Science, 9:e1757, 2023

Reference 36

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raw_fallback, observed 2026-08-15T20:38:17.399769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:38:17.011778Z digest=sha256:088b92c8b412d3f39cc7cdf84d2459daf8facd1046003af85da6cc3ced423ac6

Observation fc4348f3-88b0-4e4d-886f-8fc7fc2a73ca · outbound

This paper cites Qwen2.5 Technical Report.

SLOT: Sample-specific Language Model Optimization at Test-time Qwen2.5 Technical Report

Reference 37

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unresolved
no resolver link, observed 2026-08-15T20:38:17.016069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:17.016069Z digest=sha256:83c461b6eaffba9f879188d961e14202db74149068101cb91e570b7da0f1d0c2

Observation e3b0f746-0e29-4d0a-9b41-948f4c0e9bd4 · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

SLOT: Sample-specific Language Model Optimization at Test-time Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 38

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unresolved
no resolver link, observed 2026-08-15T20:38:17.020163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:17.020163Z digest=sha256:9c96ba7e4b790236fd0996eaebc744788055a348dbfc016ef49e6008cc651b46

Observation a45991d6-62c8-4263-b08a-3f53a23d45be · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822, 2023.

SLOT: Sample-specific Language Model Optimization at Test-time Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822, 2023

Reference 39

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unresolved
no resolver link, observed 2026-08-15T20:38:17.024323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:17.024323Z digest=sha256:33c4ee6cf2a7ca4a00e61897a9338c7d03616da61263878c84bf291077233a8b

Observation 0c2265a9-7a01-4b92-a256-86071c0e2f5f · outbound

This paper cites Benchmarking Reasoning Robustness in Large Language Models.

SLOT: Sample-specific Language Model Optimization at Test-time Benchmarking Reasoning Robustness in Large Language Models

Reference 40

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no resolver link, observed 2026-08-15T20:38:17.028835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:17.028835Z digest=sha256:6670044f28fbc51631ab3d6864017b30c8e6c0515af44c4c20a469adb9c0463c

Observation d4d6e143-130f-4034-b844-af8d5a89411e · outbound

This paper cites On Pitfalls of Test-Time Adaptation.

SLOT: Sample-specific Language Model Optimization at Test-time On Pitfalls of Test-Time Adaptation

Reference 41

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unresolved
no resolver link, observed 2026-08-15T20:38:17.033229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:17.033229Z digest=sha256:5fb7c3925cc995fece81780102b24f0ddbfffe2d27cf53c0e6895e32d36cfcb0

Observation 3bad336c-8c0b-465e-88e6-291adcbcccc7 · outbound

This paper cites TTRL: Test-Time Reinforcement Learning.

SLOT: Sample-specific Language Model Optimization at Test-time TTRL: Test-Time Reinforcement Learning

Reference 42

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malformed identifier
no resolver link, observed 2026-08-15T20:38:17.037405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:38:17.037405Z digest=sha256:838cb1b1f75177c8b8e9b113b5bb268cc15cd85e3cfd2103b916b48e0dc3816f

Pith citing papers

Observation 8fb8a73f-287e-4ea6-a7d3-064619ab26af · inbound

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle cites this paper.

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle SLOT: Sample-specific Language Model Optimization at Test-time

Reference 64

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unresolved
no resolver link, observed 2026-08-04T16:07:30.821966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:07:30.821966Z digest=sha256:3e45faa54103a8fb69eaa21b2339736d021bdc0c0e7f150311c2ac86c54ea981

Observation eac35b3f-19ea-4b2f-b0b4-0324713cec3c · inbound

Self-Reflective Generation at Test Time cites this paper.

Self-Reflective Generation at Test Time SLOT: Sample-specific Language Model Optimization at Test-time

Reference 8

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unresolved
no resolver link, observed 2026-08-04T12:41:42.525028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:41:42.525028Z digest=sha256:10107f6932a9f73375e8d4b3f8e65693dd05511023ce78d149460914fd6be1c8

Observation b3c2337d-b6b2-40a8-8e46-7a20d768bf08 · inbound

From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning cites this paper.

From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning SLOT: Sample-specific Language Model Optimization at Test-time

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:10:50.521245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T19:19:15.053725Z digest=sha256:ae40abbd17a3fdb846727b711a987d4cc8d6e5e368d890b607883a4a77b6f0b0

Observation d68e740f-b228-4c32-bb1b-63e1ccb1f9e1 · inbound

Rethinking Entropy Minimization in Test-Time Adaptation for Autoregressive Models cites this paper.

Rethinking Entropy Minimization in Test-Time Adaptation for Autoregressive Models SLOT: Sample-specific Language Model Optimization at Test-time

Reference 16

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verified exact
arxiv_id, observed 2026-05-12T00:51:14.022947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-12T00:48:47.213681Z digest=sha256:7a7fc2d584ca220996a8e48e3552ed7645171627cdbef5cbf280c56882378087

Observation dc5440c8-50dc-43f8-9f09-d48e2557360d · inbound

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation cites this paper.

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation SLOT: Sample-specific Language Model Optimization at Test-time

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-21T11:24:08.699295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T11:21:30.867480Z digest=sha256:6432a0dc0d9324d0195d70c60046c3aae6a483e4256b9f33709b0126d424aa72

Observation e802226d-8ba5-45de-8ab2-7db931ba651c · inbound

From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning cites this paper.

From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning SLOT: Sample-specific Language Model Optimization at Test-time

Reference 78

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metadata mismatch
arxiv_id, observed 2026-07-03T20:38:55.966851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-27T01:13:11.483599Z digest=sha256:d3ba5235e85d338a22a675a69696a4b8c0ac948f5bc48db3db2223fb663d3d63