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Paper Citation Record · LEDGER

LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 50 inbound Pith citation observations for arXiv:2309.11998.

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

pith.paper-citation-record.v1
2309.11998 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 50 of 50 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:52:42.871457Z

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

0 of 0 outbound references displayed

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External citation measurements

26
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2effee5e-3b1a-469e-ab4e-b6ceb4483d2f · inbound

Gemma 2: Improving Open Language Models at a Practical Size cites this paper.

Gemma 2: Improving Open Language Models at a Practical Size LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 157

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metadata mismatch
arxiv_id, observed 2026-05-10T12:11:16.536226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T12:11:16.326752Z digest=sha256:a364dbbeb6d0e817ad2b92fdc0f9fc283be50c1f86f5cdcdcc5bd724eafd2d6f

Observation a6c7dc24-c207-4948-944d-bc1e70b6a9f5 · inbound

A Survey on LLM-as-a-Judge cites this paper.

A Survey on LLM-as-a-Judge LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 221

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arxiv_id, observed 2026-05-23T17:35:43.996774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T17:33:13.394338Z digest=sha256:3903dd98a90cb93c487d1b94182f06fd25866b83dcd25244c5d09b3b5944e313

Observation 3e0b9087-bfe8-4f2c-9952-e7c04eddacba · inbound

A Survey of Scaling in Large Language Model Reasoning cites this paper.

A Survey of Scaling in Large Language Model Reasoning LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 258

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arxiv_id, observed 2026-05-22T21:22:09.145209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T21:20:07.238992Z digest=sha256:8114d7cd2c45501fe24cc2edbac65f2fee8bae19944c74559b7eb1476e6ab423

Observation c4cd9c88-6cdc-4fae-9b56-94cb8f1d9c25 · inbound

LLMs Get Lost In Multi-Turn Conversation cites this paper.

LLMs Get Lost In Multi-Turn Conversation LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 92

Resolution
verified exact
arxiv_id, observed 2026-05-14T01:11:09.380622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-14T00:57:10.262350Z digest=sha256:1080df73a3ebd3897497bbdcac962a9464cdc0e7aef8771b247eb7f4e2786c68

Observation c6d2e323-553a-4a23-93a9-e04446c795e0 · inbound

Language Matters: How Do Multilingual Input and Reasoning Paths Affect Large Reasoning Models? cites this paper.

Language Matters: How Do Multilingual Input and Reasoning Paths Affect Large Reasoning Models? LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 24

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no resolver link, observed 2026-08-07T14:52:42.871457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:52:42.871457Z digest=sha256:a85486c0b2079235bfd6e0cfa603a423ab3986ea2621fd83c7b0e3f811478f25

Observation ed9f3ccb-7d07-4760-9f1f-a91681384c04 · inbound

Understanding Refusal in Language Models with Sparse Autoencoders cites this paper.

Understanding Refusal in Language Models with Sparse Autoencoders LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 41

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no resolver link, observed 2026-08-07T12:51:09.791159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:51:09.791159Z digest=sha256:383a6b8f354f24d79d124e0d55161ed7b038791c12a987a760a6f130b94cd631

Observation f8012669-c687-4e04-bcd1-2e755e7b2226 · inbound

Evaluating the Sensitivity of LLMs to Prior Context cites this paper.

Evaluating the Sensitivity of LLMs to Prior Context LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 42

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no resolver link, observed 2026-08-07T12:45:48.207330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:48.207330Z digest=sha256:6fb7156a255984908993f92329604c57bc4ea805922bfa6f7d4193562a72122d

Observation da335835-1b20-4270-b1cf-b13241b3ddce · inbound

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? cites this paper.

Is There a Case for Conversation Optimized Tokenizers in Large Language Models? LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 14

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no resolver link, observed 2026-08-06T23:19:15.885007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:15.885007Z digest=sha256:cdc6c10afd4b3fbc60c483bb83af7de81cbc9b4050e21c83170baa9499ee432d

Observation 0abfcd2f-2d7b-478b-bbc5-bb11e48aa632 · inbound

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models cites this paper.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 38

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no resolver link, observed 2026-08-06T22:01:23.797749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:01:23.797749Z digest=sha256:2fd2632ce700a10720e952aa73f9bcf69335ce1cd75f4d716f4abae77b1c9b59

Observation 6f6d199e-5d99-47ba-bf0e-6f6b8c7185ee · inbound

Toward Real-World Chinese Psychological Support Dialogues: CPsDD Dataset and a Co-Evolving Multi-Agent System cites this paper.

Toward Real-World Chinese Psychological Support Dialogues: CPsDD Dataset and a Co-Evolving Multi-Agent System LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 17

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no resolver link, observed 2026-08-06T18:43:23.487749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:43:23.487749Z digest=sha256:220022862f447b8ea3655e13658136b13037ba7d558a96f5e0585828a0f56231

Observation 5b6ae82e-cfdb-4b88-9e7a-44bffbe31c58 · inbound

Mass-Scale Analysis of In-the-Wild Conversations Reveals Complexity Bounds on LLM Jailbreaking cites this paper.

Mass-Scale Analysis of In-the-Wild Conversations Reveals Complexity Bounds on LLM Jailbreaking LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 1

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no resolver link, observed 2026-08-06T19:56:03.839852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:56:03.839852Z digest=sha256:f6dc57c236fa2e838c5c7de1e3510771d8021c5ad0d10bb32479dc3edddfcdb2

Observation 97c3aa39-6308-4943-ac64-781035ade518 · inbound

DialogueForge: LLM Simulation of Human-Chatbot Dialogue cites this paper.

DialogueForge: LLM Simulation of Human-Chatbot Dialogue LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 41

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unresolved
no resolver link, observed 2026-08-06T15:28:46.433333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:28:46.433333Z digest=sha256:f64f2840673f47544bac73654644a96d69147bdc556bbf3356ec6a48dec0ad6c

Observation c32e457e-1f38-4c65-82f6-c89a6e99597f · inbound

Sandwich: Joint Configuration Search and Hot-Switching for Efficient CPU LLM Serving cites this paper.

Sandwich: Joint Configuration Search and Hot-Switching for Efficient CPU LLM Serving LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:11:43.925414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T15:08:15.328986Z digest=sha256:05a9df384c103b98c7e2ec44ba3a2613c6da53fba99414238988306bca305672

Observation f8c97b15-ea36-4309-aa4f-247547c64fa7 · inbound

TweakLLM: A Routing Architecture for Dynamic Tailoring of Cached Responses cites this paper.

TweakLLM: A Routing Architecture for Dynamic Tailoring of Cached Responses LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 13

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no resolver link, observed 2026-08-06T10:32:40.855458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:32:40.855458Z digest=sha256:85ea4f0b96449101d90c1c014890465e94e4fd9f31f53246fd5ff3fc67577a61

Observation 75b715a5-0439-4c50-a228-646dbe60ca2f · inbound

Improving Aviation Safety Analysis: Automated HFACS Classification Using Reinforcement Learning with Group Relative Policy Optimization cites this paper.

Improving Aviation Safety Analysis: Automated HFACS Classification Using Reinforcement Learning with Group Relative Policy Optimization LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 38

Resolution
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no resolver link, observed 2026-08-05T14:33:13.529712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:33:13.529712Z digest=sha256:51ed81561c8d1389d0c62e4b8396bb0021a715ae9664ff1ba9cf678a545f8435

Observation 54c6e2d0-3ba0-4a08-991e-f9b5024ae867 · inbound

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality cites this paper.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 81

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no resolver link, observed 2026-08-04T17:57:07.656222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.656222Z digest=sha256:042c7bf8603b4d1d628f70c8f6f2f3b4557407217caf0d64c1f495f35dacd9a0

Observation 3d3bcbbc-6b1e-4427-ad7b-013492ec7d82 · inbound

A global log for medical AI cites this paper.

A global log for medical AI LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 2024

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no resolver link, observed 2026-08-04T11:34:11.744818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:34:11.744818Z digest=sha256:cee47a8ee6ef970d0f8a5c1c0e3cff032ea6265fa28c254efc329d140b1abc47

Observation dae92762-4ad7-4c9c-99c5-c702302fdf50 · inbound

Auditing LLM Editorial Bias in News Media Exposure cites this paper.

Auditing LLM Editorial Bias in News Media Exposure LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 65

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no resolver link, observed 2026-08-04T07:01:35.841685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:01:35.841685Z digest=sha256:27b1b76eb76e7152a58dd457580706b9919dc3f14761c1c1c0e39e6923b1758e

Observation 4ce9a0ef-e085-4c78-b381-3f76bfa96a40 · inbound

NVIDIA Nemotron 3: Efficient and Open Intelligence cites this paper.

NVIDIA Nemotron 3: Efficient and Open Intelligence LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 19

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metadata mismatch
arxiv_id, observed 2026-05-18T01:40:42.344578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-18T01:40:42.190369Z digest=sha256:7becde395ddde8e3568620f4ef9af559c8a88e96c4462d5d66a8167f3af2416a

Observation ff790e81-bf4f-4b0b-bde0-13b7cff261b4 · inbound

SuperInfer: SLO-Aware Rotary Scheduling and Memory Management for LLM Inference on Superchips cites this paper.

SuperInfer: SLO-Aware Rotary Scheduling and Memory Management for LLM Inference on Superchips LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 26

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verified exact
arxiv_id, observed 2026-05-21T15:30:17.992775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T15:26:01.283448Z digest=sha256:73b7f4a16d9b8b04a2f6248aea1fc35f0722f001c01968aeb485d97bac8c3104

Observation f5ea8733-0593-459e-8e5c-ad1d4d3b9c4b · inbound

Analytical Provisioning for Attention-FFN Disaggregated LLM Serving under Stochastic Workloads cites this paper.

Analytical Provisioning for Attention-FFN Disaggregated LLM Serving under Stochastic Workloads LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 13

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verified exact
arxiv_id, observed 2026-05-16T09:57:43.059960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T09:53:13.057587Z digest=sha256:5d98da52d82588ebf3ef0f42bc6f30b8a1e51aaae927e08ec1d8ab258853ea5a

Observation e3db547c-5bb8-433f-b229-5906a2f411c6 · inbound

After Talking with 1,000 Personas: Learning Preference-Aligned Proactive Assistants From Large-Scale Persona Interactions cites this paper.

After Talking with 1,000 Personas: Learning Preference-Aligned Proactive Assistants From Large-Scale Persona Interactions LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 60

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no resolver link, observed 2026-08-03T04:54:13.151403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T04:54:13.151403Z digest=sha256:cae3f134c4457708033f948386b66fee8cd0fa6f69f8954924401c8e085f78fa

Observation a78a4497-6545-43be-b3b7-67f239523d51 · inbound

Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders cites this paper.

Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 61

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no resolver link, observed 2026-08-03T01:17:12.013304Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:17:12.013304Z digest=sha256:7c6c979060af1239cc7c3de493d93ca1f41c0cded9fe910fcee7fe5b73abec9c

Observation 73349bf9-63ce-4a28-8114-66623c7b2aa6 · inbound

Language Model Goal Selection Differs from Humans' in a Self-Directed Learning Task cites this paper.

Language Model Goal Selection Differs from Humans' in a Self-Directed Learning Task LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 23

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arxiv_id, observed 2026-05-16T06:50:42.307474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T06:48:55.986272Z digest=sha256:fe8efad52ad0c09997f82bef2630bef1e3f8448d78a11eee8068ddcafc77d653

Observation 1b28e98d-ad17-4d9b-929f-9349b61b0c88 · inbound

Comparative Characterization of KV Cache Management Strategies for LLM Inference cites this paper.

Comparative Characterization of KV Cache Management Strategies for LLM Inference LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 18

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metadata mismatch
arxiv_id, observed 2026-05-10T23:45:53.184006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:52:37.554690Z digest=sha256:acfb9e3aad877bbf6859087a1cca624cce9f88552173872bc371b7950433d02e

Observation c2c02e52-d481-4252-8859-cfbdf556b776 · inbound

SAGE: A Service Agent Graph-guided Evaluation Benchmark cites this paper.

SAGE: A Service Agent Graph-guided Evaluation Benchmark LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 67

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arxiv_id, observed 2026-05-11T08:21:00.770684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T16:41:23.956104Z digest=sha256:61302af5d3be738a14e5fc8f3b265a867c6c37759e4135b853b9cf676c5b0a5b

Observation a8124d55-4ee4-4600-992f-e1c2f9bbf22b · inbound

Flow-Controlled Scheduling for LLM Inference with Provable Stability Guarantees cites this paper.

Flow-Controlled Scheduling for LLM Inference with Provable Stability Guarantees LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 30

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metadata mismatch
arxiv_id, observed 2026-05-11T09:46:03.074337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:51:11.343200Z digest=sha256:7873930dd6fc0b0ef8d135a028b28912841c52e1179ace91dae2a34290962985

Observation 06e1ae6d-f76b-45ee-bbae-6977dfeb9721 · inbound

Predictive Multi-Tier Memory Management for KV Cache in Large-Scale GPU Inference cites this paper.

Predictive Multi-Tier Memory Management for KV Cache in Large-Scale GPU Inference LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 40

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metadata mismatch
arxiv_id, observed 2026-05-10T10:14:10.675111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T05:01:02.726796Z digest=sha256:01544c2b65fd3e6257a9cbc6e029152187ab4aa6996f70961f097a436db3eaed

Observation 8af6b0a1-0440-407a-ac8c-0787d6bc7d14 · inbound

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning cites this paper.

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 38

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verified exact
arxiv_id, observed 2026-05-12T10:26:29.131985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T06:12:37.845017Z digest=sha256:9bc32285fe3063f232dc4b37376037e77c4726e4e573d929a7d7b99dc047f867

Observation 6a0a145a-abb9-425f-8324-978da47229c3 · inbound

Latent Adversarial Detection: Adaptive Probing of LLM Activations for Multi-Turn Attack Detection cites this paper.

Latent Adversarial Detection: Adaptive Probing of LLM Activations for Multi-Turn Attack Detection LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 2

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metadata mismatch
arxiv_id, observed 2026-05-12T10:11:28.676669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T07:06:03.049639Z digest=sha256:392594c8396feb3f37a96cae0719d67454beaf69d99174c6452800242329e448

Observation 566b31c9-83b4-4ef5-adf4-d2e363b6a0e6 · inbound

Test-Time Speculation cites this paper.

Test-Time Speculation LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 35

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metadata mismatch
arxiv_id, observed 2026-05-12T04:21:22.710988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T04:20:15.459967Z digest=sha256:66efc559b00e0e51bc9d7423d4ad87d95dff26ba75a702f6d5a08e51dd6c2b38

Observation a9327a56-e889-4f02-8eb4-05e0b4f80b6b · inbound

Test-Time Speculation cites this paper.

Test-Time Speculation LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T22:54:09.735662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T22:53:56.914556Z digest=sha256:8a01bd76c24c9d4929a173bed94ae80008c6b7e4f0e21ae73559176a463c86d4

Observation 9ce70a6e-18cc-4d0d-895c-092c4f02924e · inbound

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs cites this paper.

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 30

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metadata mismatch
arxiv_id, observed 2026-05-12T06:56:31.247022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T03:46:48.498800Z digest=sha256:704fdff324f28e58c4547001cc779bc7c7bdb702b70f2ca9be982e9ed6e7ceb8

Observation b369bc21-5b15-45ea-b392-c3f707031277 · inbound

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs cites this paper.

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 30

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unresolved
no resolver link, observed 2026-08-02T14:31:12.736399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:31:12.736399Z digest=sha256:43034225375262608d88d6ed5213b045db316f266e5e7e5cd0437c736f8ebcac

Observation 23a62907-e910-45b2-bfd9-a07f43494416 · inbound

EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions cites this paper.

EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 3

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metadata mismatch
arxiv_id, observed 2026-06-30T16:24:55.257713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T16:22:02.166135Z digest=sha256:5458d3d0ced2ff7056ab23b313532d25b27b1eee72167430d63fbd64b68eb8bf

Observation a87fd0d1-e197-4ae4-a778-e79ec488df0d · inbound

Kavier: Exploring Performance, Sustainability, and Efficiency of LLM Ecosystems under Inference through Cache-Aware Discrete-Event Simulation cites this paper.

Kavier: Exploring Performance, Sustainability, and Efficiency of LLM Ecosystems under Inference through Cache-Aware Discrete-Event Simulation LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T23:34:04.628815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T23:27:08.631657Z digest=sha256:5e2e9a73f4a8c4a67399b0b5d510c8f280571cfb11faf50556425061b0f52164

Observation 6a5cb03a-6ab2-42ea-87ad-7548f0c93755 · inbound

SeDT: Sentence-Transformer Decision-Transformer Conditioning for Multi-Turn Conversation Reliability cites this paper.

SeDT: Sentence-Transformer Decision-Transformer Conditioning for Multi-Turn Conversation Reliability LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T18:53:51.637982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T18:45:40.697579Z digest=sha256:e29f7ce588e73055331561f5990840eab677e76c1b8aaa0fa03f51cd8d91a4cd

Observation b7946e74-caf9-4a54-b8c9-ede5257b5c3c · inbound

Cybersecurity AI (CAI) Dataset cites this paper.

Cybersecurity AI (CAI) Dataset LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 62

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verified exact
arxiv_id, observed 2026-06-29T12:13:26.842915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T12:07:49.656453Z digest=sha256:694ec93abd7b59cf74564bf9f2290435b0650c3b2919a95444daa25744d3a782

Observation a3627ec1-bdcb-477b-8c75-1362c5ef0ea1 · inbound

End-to-End Context Compression at Scale cites this paper.

End-to-End Context Compression at Scale LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 95

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metadata mismatch
arxiv_id, observed 2026-07-03T01:17:31.540635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T16:36:54.699174Z digest=sha256:ea95c16afadb8ede1e2e6091296e7c8a81cb2739554c3e5646facb366c7fbf8b

Observation fcc3d7fb-3f1c-4c74-8509-8c2d755597c5 · inbound

Beyond Third-Person Audits: Situated Interaction Auditing for User-Centered LLM Bias Research cites this paper.

Beyond Third-Person Audits: Situated Interaction Auditing for User-Centered LLM Bias Research LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T13:28:18.896792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T08:03:18.763513Z digest=sha256:20acf9fc4a8ac5cd890e80e0bafa5eb373a1c82b039c7dc67fdd3b2fdb28869a

Observation 9056253d-b644-4f96-b5ec-69c65c3b099d · inbound

AI Fiction in the Wild cites this paper.

AI Fiction in the Wild LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 146

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verified exact
arxiv_id, observed 2026-06-26T09:09:15.759267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T09:05:54.690083Z digest=sha256:73de2e11ef89d196083b5422cb6fb93adc631e633d22cd8d8eb7ae7bcceb4a13

Observation cd51c28a-b12d-4c11-b952-c686e1c9d9e9 · inbound

Detecting and Controlling Sycophancy with Cascading Linear Features cites this paper.

Detecting and Controlling Sycophancy with Cascading Linear Features LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 20

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malformed identifier
arxiv_id, observed 2026-07-04T15:49:57.092348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T01:24:56.600219Z digest=sha256:1d3044191378793b5672599e983f1a61ce13af8e094a6cc64c7802bab6baa740

Observation 8f59a3c9-dbaf-4528-912f-4e428514e134 · inbound

At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization cites this paper.

At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 55

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verified exact
arxiv_id, observed 2026-06-26T01:28:50.489454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T01:27:39.812228Z digest=sha256:a3cc14495840f98999c012f94d2798f22879f4897653514b0fd5052a2070e83b

Observation a1d22051-0308-4266-a051-a2b5dae2e822 · inbound

Turn-Averaged SAEs for Feature Discovery and Long-Context Attribution cites this paper.

Turn-Averaged SAEs for Feature Discovery and Long-Context Attribution LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 23

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metadata mismatch
arxiv_id, observed 2026-07-01T15:35:48.355521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T01:20:29.026464Z digest=sha256:318c6eb4a4d8f9d8518c091f7f3151eb8817e6363cb74f60f52c3e5cda2e13e7

Observation 81ff348b-798b-41ed-977c-18c2823e3782 · inbound

KernelFlume: Elastic Core-Attention Scaling for Agentic Long-Context Decoding cites this paper.

KernelFlume: Elastic Core-Attention Scaling for Agentic Long-Context Decoding LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-06-30T03:04:14.246323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T02:54:11.777615Z digest=sha256:922cf9b3546d5e8e58f6b5aa4bffe0e14d3937a8b1cdd0eb47630966fbd3c6ab

Observation 0718dd6e-a337-4eb6-9e03-0a78f7fc2e1f · inbound

The One-Word Census: Answer-Choice Conformity Across 44 Language Models cites this paper.

The One-Word Census: Answer-Choice Conformity Across 44 Language Models LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 33

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unresolved
no resolver link, observed 2026-08-02T06:23:49.144748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:23:49.144748Z digest=sha256:547388304b4ef472d2468e804a72469368631180f65233a71f8c5c9c2f476efd

Observation 3222fcf7-dcc5-422f-80f5-6e7fafca8aec · inbound

Economic Evaluations of Language Models cites this paper.

Economic Evaluations of Language Models LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 82

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unresolved
no resolver link, observed 2026-08-02T09:51:06.015416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T09:51:06.015416Z digest=sha256:871c7c9613eaebdf7a55c6165b5afdb3f4c648f3e69f826a75f1c6b47352d9c8

Observation 718a4ffc-6eed-4416-ada0-1ad21d066cc0 · inbound

RH-RAG: Trustworthy Long-Form Generation for Privacy-Constrained Settings cites this paper.

RH-RAG: Trustworthy Long-Form Generation for Privacy-Constrained Settings LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 44

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no resolver link, observed 2026-08-06T00:24:46.403756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:24:46.403756Z digest=sha256:7ff05991223026d31fa7a0c072333c8a607e122091885079fa48459e9cb29a75

Observation cdef2cf6-f521-4abe-b227-83ae8c4a340d · inbound

Efficiency and Cost Alignment in Batched LLM Serving via Resource-Fair Scheduling cites this paper.

Efficiency and Cost Alignment in Batched LLM Serving via Resource-Fair Scheduling LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 36

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unresolved
no resolver link, observed 2026-08-04T10:54:03.201603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:54:03.201603Z digest=sha256:2ea53815158881664df85907ed5f3f7f0e782d49a7ce150c0e2ba404ddb1986a

Observation e6031a77-6aa1-4056-adf4-b268e5de1dc9 · inbound

CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement cites this paper.

CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 71

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unresolved
no resolver link, observed 2026-08-05T10:23:58.898632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T10:23:58.898632Z digest=sha256:dad5816197a4b753d2227f4e2cdcd7110eb8def1282d50b458acb5dedddc4837