Paper Citation Record · LEDGER

Towards Understanding Sycophancy in Language Models

As of 11 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 100 inbound Pith citation observations for arXiv:2310.13548.

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

pith.paper-citation-record.v1
2310.13548 v4

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-11T06:26:29.196349Z

measured 129 of 129 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 100 of 255 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T01:04:06.622696Z

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

29 of 29 outbound references displayed

verified exact14
verified fuzzy8
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

91
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 06a1e84d-6252-44e3-8c77-7c416cd66f1f · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Towards Understanding Sycophancy in Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T06:26:29.367756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b8b401bf-361d-43d4-993c-33504914f439 · outbound

This paper cites Measuring Progress on Scalable Oversight for Large Language Models.

Towards Understanding Sycophancy in Language Models Measuring Progress on Scalable Oversight for Large Language Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-17T15:01:41.422297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0be202c9-f4f0-46d3-baf7-0ca470f14c8c · outbound

This paper cites an unresolved cited work.

Towards Understanding Sycophancy in Language Models Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-05-11T06:26:29.607674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8aa8bd7e-9a1d-4eb7-9f4f-b0616826c683 · outbound

This paper cites cc/paper_files/paper/2017/file/d5e2c0adad503c91f91df240d0cd4e49-Paper.pdf.

Towards Understanding Sycophancy in Language Models cc/paper_files/paper/2017/file/d5e2c0adad503c91f91df240d0cd4e49-Paper.pdf

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-11T06:26:29.566711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3804e699-6c18-420f-a666-694a6bef858b · outbound

This paper cites Scaling Laws for Reward Model Overoptimization.

Towards Understanding Sycophancy in Language Models Scaling Laws for Reward Model Overoptimization

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:04:53.407177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 585d14de-d147-4067-9ef8-6c8578009894 · outbound

This paper cites Improving alignment of dialogue agents via targeted human judgements.

Towards Understanding Sycophancy in Language Models Improving alignment of dialogue agents via targeted human judgements

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-14T17:54:02.323766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 329035fd-2965-4f38-96e5-bb1541504824 · outbound

This paper cites Podcast episodes between October 2020 and September.

Towards Understanding Sycophancy in Language Models Podcast episodes between October 2020 and September

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.546055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7dd26a4f-770f-4ebc-852c-bc243a160bc9 · outbound

This paper cites The False Promise of Imitating Proprietary LLMs.

Towards Understanding Sycophancy in Language Models The False Promise of Imitating Proprietary LLMs

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:54:31.902059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 516070d1-c469-45e9-8dce-0182294a6827 · outbound

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

Towards Understanding Sycophancy in Language Models Measuring Mathematical Problem Solving With the MATH Dataset

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-11T06:26:29.383217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c59668c5-e4a3-475b-ae45-4ce0524dd658 · outbound

This paper cites On the Sensitivity of Reward Inference to Misspecified Human Models.

Towards Understanding Sycophancy in Language Models On the Sensitivity of Reward Inference to Misspecified Human Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.395333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 948ff31b-5cc2-4470-a352-b23a7baebca8 · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

Towards Understanding Sycophancy in Language Models TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:00:28.883814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 30866190-b7ec-43f6-9755-a980371398a7 · outbound

This paper cites Understanding the Effects of RLHF on LLM Generalisation and Diversity.

Towards Understanding Sycophancy in Language Models Understanding the Effects of RLHF on LLM Generalisation and Diversity

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-19T02:34:44.407176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7074416a-c18e-48bb-8383-81ad7394c936 · outbound

This paper cites URLhttps://doi.org/10.18653/v1/2022.acl-long.229.

Towards Understanding Sycophancy in Language Models URLhttps://doi.org/10.18653/v1/2022.acl-long.229

Reference 13

Resolution: verified exact; doi, observed 2026-05-11T06:26:29.315352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1206e60f-cd8e-43c5-bc72-4c349ae9991d · outbound

This paper cites Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems.

Towards Understanding Sycophancy in Language Models Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.432244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 55ac8bbf-4f4a-4a7c-823d-7cdb49cc5575 · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

Towards Understanding Sycophancy in Language Models WebGPT: Browser-assisted question-answering with human feedback

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T06:26:29.442512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9a677176-86da-4f30-b893-a582fdb0a294 · outbound

This paper cites Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro.

Towards Understanding Sycophancy in Language Models Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.456900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2d036253-682d-4382-b81e-a9070bdc0173 · outbound

This paper cites Question Decomposition Improves the Faithfulness of Model-Generated Reasoning.

Towards Understanding Sycophancy in Language Models Question Decomposition Improves the Faithfulness of Model-Generated Reasoning

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:26:29.467153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 846fa01d-f1b0-418d-be07-d9303aab27d5 · outbound

This paper cites Self-critiquing models for assisting human evaluators.

Towards Understanding Sycophancy in Language Models Self-critiquing models for assisting human evaluators

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:25:41.981797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aa2c2c43-b07c-4c22-9e98-7300e3b40049 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Towards Understanding Sycophancy in Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-11T06:26:29.482594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51713a0b-5d23-48ae-9d8f-371fd95ed420 · outbound

This paper cites Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting.

Towards Understanding Sycophancy in Language Models Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T12:01:19.882845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2a4d8225-f3e7-4eab-b18a-033f1dec01a5 · outbound

This paper cites Are you sure?.

Towards Understanding Sycophancy in Language Models Are you sure?

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-11T06:26:29.600023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation abe62484-3389-4ea4-aebf-b38dc3bdaa19 · outbound

This paper cites {first_comment}.

Towards Understanding Sycophancy in Language Models {first_comment}

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-11T06:26:29.603979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b0a2b541-02a2-492f-b94b-3bc4f3ce6992 · outbound

This paper cites Are you sure?.

Towards Understanding Sycophancy in Language Models Are you sure?

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-11T06:26:29.611660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8e2cefbd-793e-45bc-95b0-de7e620c60b6 · outbound

This paper cites an unresolved cited work.

Towards Understanding Sycophancy in Language Models Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-05-11T06:26:29.570863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation df2167b2-09df-4b01-a6eb-7681920e5d7d · outbound

This paper cites Are you sure?.

Towards Understanding Sycophancy in Language Models Are you sure?

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-11T06:26:29.574724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aad83b09-4684-431f-9792-04bbd2442d69 · outbound

This paper cites an unresolved cited work.

Towards Understanding Sycophancy in Language Models Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-05-11T06:26:29.580821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 850458c2-73fe-401d-901b-33be83fa375b · outbound

This paper cites Are you sure?.

Towards Understanding Sycophancy in Language Models Are you sure?

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-11T06:26:29.584801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 12408e6b-e10f-41d1-a24a-810c85222fb3 · outbound

This paper cites matches a user’s beliefs, biases, and preferences.

Towards Understanding Sycophancy in Language Models matches a user’s beliefs, biases, and preferences

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-11T06:26:29.590809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2ab6cb47-cf75-4bb0-9880-678c3a64291e · outbound

This paper cites the Earth’s crust is a solid, unbroken shell.

Towards Understanding Sycophancy in Language Models the Earth’s crust is a solid, unbroken shell

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-11T06:26:29.595793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation fe7dadc4-83c5-4090-a177-5e3f7b6e53a6 · inbound

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions cites this paper.

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions Towards Understanding Sycophancy in Language Models

Reference 287

Resolution: metadata mismatch; local_arxiv, observed 2026-05-13T02:47:07.663376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3a7f5de1-0feb-4bf7-b453-e335b530db3a · inbound

A theory of appropriateness with applications to generative artificial intelligence cites this paper.

A theory of appropriateness with applications to generative artificial intelligence Towards Understanding Sycophancy in Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T01:04:06.622696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00ec60a4-1eda-4a43-9875-3b600fd84f18 · inbound

Open Problems in Machine Unlearning for AI Safety cites this paper.

Open Problems in Machine Unlearning for AI Safety Towards Understanding Sycophancy in Language Models

Reference 113

Resolution: unresolved; no resolver link, observed 2026-08-10T21:24:10.556478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69380e8a-76c8-426c-be72-1cde0bbabcd1 · inbound

Emergence of human-like polarization among large language model agents cites this paper.

Emergence of human-like polarization among large language model agents Towards Understanding Sycophancy in Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T21:20:27.477105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e186f360-090f-4349-b80a-c3a84bc0adab · inbound

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy cites this paper.

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy Towards Understanding Sycophancy in Language Models

Reference 176

Resolution: unresolved; no resolver link, observed 2026-08-10T20:05:12.562654Z

Source-reported events for the cited work

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Observation b82dd49e-e50e-46c1-9825-f29f98496273 · inbound

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment cites this paper.

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment Towards Understanding Sycophancy in Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T19:55:50.737082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e5e7b8b-25c5-47bc-8ab3-87be46909143 · inbound

Examining Alignment of Large Language Models through Representative Heuristics: The Case of Political Stereotypes cites this paper.

Examining Alignment of Large Language Models through Representative Heuristics: The Case of Political Stereotypes Towards Understanding Sycophancy in Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T15:18:19.150186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2b50e1b-3ec9-4c3d-93e6-c568538e35dd · inbound

Better Slow than Sorry: Introducing Positive Friction for Reliable Dialogue Systems cites this paper.

Better Slow than Sorry: Introducing Positive Friction for Reliable Dialogue Systems Towards Understanding Sycophancy in Language Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T04:47:29.302683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 299e982f-0e7f-499e-ba11-40b46849b9fd · inbound

Why human-AI relationships need socioaffective alignment cites this paper.

Why human-AI relationships need socioaffective alignment Towards Understanding Sycophancy in Language Models

Reference 116

Resolution: unresolved; no resolver link, observed 2026-08-09T11:53:43.820296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df83911b-8f55-40ed-a75a-cbe9207ffd91 · inbound

Thinking beyond the anthropomorphic paradigm benefits LLM research cites this paper.

Thinking beyond the anthropomorphic paradigm benefits LLM research Towards Understanding Sycophancy in Language Models

Reference 80

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 337a7563-7d91-41b5-b62c-e65f2f6bb52e · inbound

AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting cites this paper.

AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting Towards Understanding Sycophancy in Language Models

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-05-23T02:57:26.367489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7fc3778f-ab1c-4727-9ff9-6212de168d44 · inbound

AI-Augmented LLMs Achieve Therapist-Level Responses in Motivational Interviewing cites this paper.

AI-Augmented LLMs Achieve Therapist-Level Responses in Motivational Interviewing Towards Understanding Sycophancy in Language Models

Reference 138

Resolution: unresolved; no resolver link, observed 2026-08-07T14:52:55.899283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 239de3a9-6934-42b7-88d3-c67f103a764f · inbound

Evaluating Intra-firm LLM Alignment Strategies in Business Contexts cites this paper.

Evaluating Intra-firm LLM Alignment Strategies in Business Contexts Towards Understanding Sycophancy in Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:28:03.507897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db85ade9-021f-4d08-ba0c-b583862b3326 · inbound

Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs) cites this paper.

Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs) Towards Understanding Sycophancy in Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:12.346980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 376821a5-690f-42ca-9a69-e0cbea111ca5 · inbound

Conservative Bias in Large Language Models: Measuring Relation Predictions cites this paper.

Conservative Bias in Large Language Models: Measuring Relation Predictions Towards Understanding Sycophancy in Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:26:07.247180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb3c9b11-77cd-4515-9821-a008d0c291a1 · inbound

"Check My Work?": Measuring Sycophancy in a Simulated Educational Context cites this paper.

"Check My Work?": Measuring Sycophancy in a Simulated Educational Context Towards Understanding Sycophancy in Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:36:07.179321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f80abd4b-c4ec-4e6a-a5db-cc57c0a0b564 · inbound

AssertBench: A Benchmark for Evaluating Self-Assertion in Large Language Models cites this paper.

AssertBench: A Benchmark for Evaluating Self-Assertion in Large Language Models Towards Understanding Sycophancy in Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:48:18.743441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 270d24db-fe13-475b-95c7-9967678625b7 · inbound

The Rise of AI Companions: Interaction with AI Companions and Psychological Well-being cites this paper.

The Rise of AI Companions: Interaction with AI Companions and Psychological Well-being Towards Understanding Sycophancy in Language Models

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-19T09:22:16.032256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8712f5f9-4c4e-492b-8b6d-989ca7ade56e · inbound

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning cites this paper.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning Towards Understanding Sycophancy in Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:49:26.199238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bc85edd-9b99-450c-b761-5bdc94cb39b2 · inbound

How Overconfidence in Initial Choices and Underconfidence Under Criticism Modulate Change of Mind in Large Language Models cites this paper.

How Overconfidence in Initial Choices and Underconfidence Under Criticism Modulate Change of Mind in Large Language Models Towards Understanding Sycophancy in Language Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:54.638875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5778aff4-0b18-4d77-9a21-4daeff189325 · inbound

Dr.Copilot: A Multi-Agent Prompt Optimized Assistant for Improving Patient-Doctor Communication in Romanian cites this paper.

Dr.Copilot: A Multi-Agent Prompt Optimized Assistant for Improving Patient-Doctor Communication in Romanian Towards Understanding Sycophancy in Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T17:17:24.416683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8649ffeb-edf7-41dd-bf06-e35c8d85d5df · inbound

WebGuard: Building a Generalizable Guardrail for Web Agents cites this paper.

WebGuard: Building a Generalizable Guardrail for Web Agents Towards Understanding Sycophancy in Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T16:12:50.339267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a1a5579-dcf3-487f-b11b-651db1286378 · inbound

Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report cites this paper.

Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report Towards Understanding Sycophancy in Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T15:14:22.951866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0db4843-088f-4a35-bb1b-a0df4e4128de · inbound

Safety Features for a Centralised AGI Project cites this paper.

Safety Features for a Centralised AGI Project Towards Understanding Sycophancy in Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:55.651236Z

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Observation 3a8320f0-f3eb-4b85-ae25-8c320865a0cf · inbound

BAR Conjecture: the Feasibility of Inference Budget-Constrained LLM Services with Authenticity and Reasoning cites this paper.

BAR Conjecture: the Feasibility of Inference Budget-Constrained LLM Services with Authenticity and Reasoning Towards Understanding Sycophancy in Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T11:04:47.211412Z

Source-reported events for the cited work

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Observation 66f6d03e-1bfd-4b2e-bd6b-bdd19e6b916d · inbound

A Survey on Data Security in Large Language Models cites this paper.

A Survey on Data Security in Large Language Models Towards Understanding Sycophancy in Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T05:05:02.851620Z

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Observation 8dc4231d-f604-4f96-8269-22855c942db2 · inbound

Exploring the Challenges and Opportunities of AI-assisted Codebase Generation cites this paper.

Exploring the Challenges and Opportunities of AI-assisted Codebase Generation Towards Understanding Sycophancy in Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T21:48:01.694534Z

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Unavailable: canonical work link unavailable.

Observation 42bea56d-127a-4cba-8ef5-c45f5814a891 · inbound

Lexical Hints of Accuracy in LLM Reasoning Chains cites this paper.

Lexical Hints of Accuracy in LLM Reasoning Chains Towards Understanding Sycophancy in Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T18:48:51.499083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1354682-1165-4851-a828-1c798c759a6d · inbound

SATORI: Static Test Oracle Generation for REST APIs cites this paper.

SATORI: Static Test Oracle Generation for REST APIs Towards Understanding Sycophancy in Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T17:26:48.564081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3238fac-a24c-45a3-994d-19a9a6d254d1 · inbound

BASIL: Bayesian Assessment of Sycophancy in LLMs cites this paper.

BASIL: Bayesian Assessment of Sycophancy in LLMs Towards Understanding Sycophancy in Language Models

Reference 10

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T21:56:51.983450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2a5b2435-3baf-4cb5-982e-b69d4fdaeaf2 · inbound

School of Reward Hacks: Hacking harmless tasks generalizes to misaligned behavior in LLMs cites this paper.

School of Reward Hacks: Hacking harmless tasks generalizes to misaligned behavior in LLMs Towards Understanding Sycophancy in Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T16:57:09.417680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d8cdd3d-85f0-4a46-a83f-2fc5c43bfb96 · inbound

Principled Detection of Hallucinations in Large Language Models via Multiple Testing cites this paper.

Principled Detection of Hallucinations in Large Language Models via Multiple Testing Towards Understanding Sycophancy in Language Models

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-18T20:46:51.597802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 32b354e8-4517-44c0-9f37-143e6d2a171a · inbound

Sycophancy as compositions of Atomic Psychometric Traits cites this paper.

Sycophancy as compositions of Atomic Psychometric Traits Towards Understanding Sycophancy in Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:50.583217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f9c4bf3-b53c-40b5-8b7b-a35faa0ef263 · inbound

Reliable Weak-to-Strong Monitoring of LLM Agents cites this paper.

Reliable Weak-to-Strong Monitoring of LLM Agents Towards Understanding Sycophancy in Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-05T15:53:53.970356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee0326bb-ff3d-4e86-ac02-f7e907d7b1ce · inbound

Measuring and mitigating overreliance to build human-compatible AI cites this paper.

Measuring and mitigating overreliance to build human-compatible AI Towards Understanding Sycophancy in Language Models

Reference 107

Resolution: verified exact; local_arxiv, observed 2026-05-21T22:40:43.403858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation be428a8c-4059-4b1e-9c36-fc01e2112aa7 · inbound

Inteligencia Artificial jur\'idica y el desaf\'io de la veracidad: an\'alisis de alucinaciones, optimizaci\'on de RAG y principios para una integraci\'on responsable cites this paper.

Inteligencia Artificial jur\'idica y el desaf\'io de la veracidad: an\'alisis de alucinaciones, optimizaci\'on de RAG y principios para una integraci\'on responsable Towards Understanding Sycophancy in Language Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-04T19:07:41.254077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4239b79-86f6-44cd-a291-d8b540c36271 · inbound

The Morality of Probability: How Implicit Moral Biases in LLMs May Shape the Future of Human-AI Symbiosis cites this paper.

The Morality of Probability: How Implicit Moral Biases in LLMs May Shape the Future of Human-AI Symbiosis Towards Understanding Sycophancy in Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T18:01:56.854499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ebdf171-434d-4d73-8962-8d0d6cf5c0bf · inbound

Benchmarking and Mitigating Sycophancy in Medical Vision Language Models cites this paper.

Benchmarking and Mitigating Sycophancy in Medical Vision Language Models Towards Understanding Sycophancy in Language Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-18T14:06:27.398202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 99d46a7e-118f-4945-95a2-a49e285fcae9 · inbound

Benchmarking and Mitigating Sycophancy in Medical Vision Language Models cites this paper.

Benchmarking and Mitigating Sycophancy in Medical Vision Language Models Towards Understanding Sycophancy in Language Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-21T21:30:39.306333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2a5d1655-245d-4254-8ebe-228691202dc9 · inbound

The Chameleon Nature of LLMs: Quantifying Multi-Turn Stance Instability in Search-Enabled Language Models cites this paper.

The Chameleon Nature of LLMs: Quantifying Multi-Turn Stance Instability in Search-Enabled Language Models Towards Understanding Sycophancy in Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T09:15:48.616354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03515745-9e3e-4822-aeee-bd4f41c47f8a · inbound

Human-AI Complementarity: A Goal for Amplified Oversight cites this paper.

Human-AI Complementarity: A Goal for Amplified Oversight Towards Understanding Sycophancy in Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T07:21:22.535843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0891fa8f-241d-4331-a987-fdbc95b00893 · inbound

From Fact to Judgment: Investigating the Impact of Task Framing on LLM Conviction in Dialogue Systems cites this paper.

From Fact to Judgment: Investigating the Impact of Task Framing on LLM Conviction in Dialogue Systems Towards Understanding Sycophancy in Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T06:48:38.233633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46f8843d-72b0-4adc-8b0a-efc6f2dab12c · inbound

Personality Pairing Improves Human-AI Collaboration cites this paper.

Personality Pairing Improves Human-AI Collaboration Towards Understanding Sycophancy in Language Models

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-17T20:12:04.096252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 803b6915-7f06-4cfc-994b-466858ea8bd7 · inbound

Personality Pairing Improves Human-AI Collaboration cites this paper.

Personality Pairing Improves Human-AI Collaboration Towards Understanding Sycophancy in Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T21:43:43.573897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1cba9f9-b963-402d-8ddd-a3f1ccecf800 · inbound

The Impact of Off-Policy Training Data on Probe Generalisation cites this paper.

The Impact of Off-Policy Training Data on Probe Generalisation Towards Understanding Sycophancy in Language Models

Reference 35

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T20:30:11.664946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 31237818-e317-4df1-97e4-23fbc84f44e6 · inbound

Epistemic Familiarity is Associated With Belief Stability in Large Language Models cites this paper.

Epistemic Familiarity is Associated With Belief Stability in Large Language Models Towards Understanding Sycophancy in Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T20:37:41.534042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3885686-e2a0-4dc6-b0b2-05585f67d104 · inbound

Safe for Whom? Rethinking How We Evaluate the Safety of LLMs for Real Users cites this paper.

Safe for Whom? Rethinking How We Evaluate the Safety of LLMs for Real Users Towards Understanding Sycophancy in Language Models

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-16T23:23:39.919584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d9bc3041-4c5d-4fbb-9c91-7290b4934175 · inbound

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org cites this paper.

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org Towards Understanding Sycophancy in Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T16:56:19.370828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfd21e6e-8b8d-49bf-a539-0124639fe5d9 · inbound

User Detection and Response Patterns of Sycophantic Behavior in Conversational AI cites this paper.

User Detection and Response Patterns of Sycophantic Behavior in Conversational AI Towards Understanding Sycophancy in Language Models

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-05-16T14:07:58.781971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bfb08858-2f46-4e35-a843-d7861f6d9c5e · inbound

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models cites this paper.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Towards Understanding Sycophancy in Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T09:37:08.296310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c0b1a5a-538f-4732-a27a-ee93e9bfc2c5 · inbound

Beyond Fixed Psychological Personas: State Beats Trait, but Language Models are State-Blind cites this paper.

Beyond Fixed Psychological Personas: State Beats Trait, but Language Models are State-Blind Towards Understanding Sycophancy in Language Models

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T12:07:50.633552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2909f4c8-9d4d-4dc3-a6f2-3afebc61b437 · inbound

Factored Causal Representation Learning for Robust Reward Modeling in RLHF cites this paper.

Factored Causal Representation Learning for Robust Reward Modeling in RLHF Towards Understanding Sycophancy in Language Models

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-05-21T14:20:13.640388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 45356c22-1b74-4fb5-b8e7-7bcf0775388c · inbound

PersistBench: When Should Long-Term Memories Be Forgotten by LLMs? cites this paper.

PersistBench: When Should Long-Term Memories Be Forgotten by LLMs? Towards Understanding Sycophancy in Language Models

Reference 3

Resolution: malformed identifier; no resolver link, observed 2026-08-03T05:52:46.614826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8492062-8ee0-4b1d-bd58-050ae2aa5ff2 · inbound

AI Chatbot Suicide Risk Detection and Response: Human Validation Study of the Open-Source VERA-MH Safety Evaluation cites this paper.

AI Chatbot Suicide Risk Detection and Response: Human Validation Study of the Open-Source VERA-MH Safety Evaluation Towards Understanding Sycophancy in Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T04:24:14.673016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c76cc6e4-a9d4-42cd-841e-ba0a9a5a5ee1 · inbound

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation cites this paper.

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation Towards Understanding Sycophancy in Language Models

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-03T03:04:44.296777Z

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Unavailable: canonical work link unavailable.

Observation 42194197-9284-4865-bb43-169eaea4c12b · inbound

CircuChain: Disentangling Competence and Compliance in LLM Circuit Analysis cites this paper.

CircuChain: Disentangling Competence and Compliance in LLM Circuit Analysis Towards Understanding Sycophancy in Language Models

Reference 19

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T10:07:43.274770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ff1ecbac-5d5c-487b-875f-5e4162f64762 · inbound

Learning When to Trust in Contextual Social Bandits cites this paper.

Learning When to Trust in Contextual Social Bandits Towards Understanding Sycophancy in Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-15T12:59:04.484292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2454c07-ad5e-4e22-9d1a-dd587c19482b · inbound

To See or To Please: Uncovering Visual Sycophancy and Split Beliefs in VLMs cites this paper.

To See or To Please: Uncovering Visual Sycophancy and Split Beliefs in VLMs Towards Understanding Sycophancy in Language Models

Reference 28

Resolution: metadata mismatch; local_arxiv, observed 2026-05-15T09:19:53.751752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eec033d5-58d4-4972-b925-5fcc9fc9d991 · inbound

Cognitive Agency Surrender: Defending Epistemic Sovereignty via Scaffolded AI Friction cites this paper.

Cognitive Agency Surrender: Defending Epistemic Sovereignty via Scaffolded AI Friction Towards Understanding Sycophancy in Language Models

Reference 39

Resolution: metadata mismatch; local_arxiv, observed 2026-05-15T00:58:25.108661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 86911a3e-9f5e-492f-812b-7ce0a19f4f61 · inbound

Using LLM-as-a-Judge/Jury to Advance Scalable, Clinically-Validated Safety Evaluations of Model Responses to Users Demonstrating Psychosis cites this paper.

Using LLM-as-a-Judge/Jury to Advance Scalable, Clinically-Validated Safety Evaluations of Model Responses to Users Demonstrating Psychosis Towards Understanding Sycophancy in Language Models

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-05-15T09:09:53.337194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fc9cfc0b-6e2c-43eb-bc07-88d5224f1da7 · inbound

SWAY: A Counterfactual Computational Linguistic Approach to Measuring and Mitigating Sycophancy cites this paper.

SWAY: A Counterfactual Computational Linguistic Approach to Measuring and Mitigating Sycophancy Towards Understanding Sycophancy in Language Models

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-13T21:48:19.237792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bbc844bf-f483-48f4-920d-c939047f33ef · inbound

Mitigating LLM biases toward spurious social contexts using direct preference optimization cites this paper.

Mitigating LLM biases toward spurious social contexts using direct preference optimization Towards Understanding Sycophancy in Language Models

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-13T20:33:14.707792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7ba934ae-ebe5-49c8-ba2e-384987ed82ea · inbound

Beyond Semantic Manipulation: Token-Space Attacks on Reward Models cites this paper.

Beyond Semantic Manipulation: Token-Space Attacks on Reward Models Towards Understanding Sycophancy in Language Models

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-13T20:33:16.838984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3f82efe1-a3b6-49e9-a9ab-5dc91f3a96f5 · inbound

PolySwarm: A Multi-Agent Large Language Model Framework for Prediction Market Trading and Latency Arbitrage cites this paper.

PolySwarm: A Multi-Agent Large Language Model Framework for Prediction Market Trading and Latency Arbitrage Towards Understanding Sycophancy in Language Models

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-13T17:08:01.608998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 190b03c6-7768-4af0-a9e8-c3e1cb9ca9c0 · inbound

Simulating the Evolution of Alignment and Values in Machine Intelligence cites this paper.

Simulating the Evolution of Alignment and Values in Machine Intelligence Towards Understanding Sycophancy in Language Models

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a0e2988-53de-4915-ba8f-f4c31a1b6233 · inbound

Pressure, What Pressure? Sycophancy Disentanglement in Language Models via Reward Decomposition cites this paper.

Pressure, What Pressure? Sycophancy Disentanglement in Language Models via Reward Decomposition Towards Understanding Sycophancy in Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1aeb082e-8208-4d37-9cf0-b414fbd7f6f6 · inbound

LLM Spirals of Delusion: A Benchmarking Audit Study of AI Chatbot Interfaces cites this paper.

LLM Spirals of Delusion: A Benchmarking Audit Study of AI Chatbot Interfaces Towards Understanding Sycophancy in Language Models

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-15T20:40:18.825441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a7148b16-3cd2-4c84-b14f-6cbbb7ae4bed · inbound

The Role of Emotional Stimuli and Intensity in Shaping Large Language Model Behavior cites this paper.

The Role of Emotional Stimuli and Intensity in Shaping Large Language Model Behavior Towards Understanding Sycophancy in Language Models

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aba39c2d-7340-4312-bc30-3eff64ea94f2 · inbound

From Debate to Decision: Conformal Social Choice for Safe Multi-Agent Deliberation cites this paper.

From Debate to Decision: Conformal Social Choice for Safe Multi-Agent Deliberation Towards Understanding Sycophancy in Language Models

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ecb60a2f-4361-4b41-a8b2-b009cec711fb · inbound

IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures cites this paper.

IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures Towards Understanding Sycophancy in Language Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 34e7d28a-adea-47fb-a19e-23d1230e4505 · inbound

IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures cites this paper.

IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures Towards Understanding Sycophancy in Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-13T00:19:33.861692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dda1616-b12e-4ee7-910b-fb41ff247f96 · inbound

Emotion Concepts and their Function in a Large Language Model cites this paper.

Emotion Concepts and their Function in a Large Language Model Towards Understanding Sycophancy in Language Models

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2d5d9a38-8c4b-4399-82d1-ab7af92bafc3 · inbound

Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces cites this paper.

Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces Towards Understanding Sycophancy in Language Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4aa36881-5dd1-413d-954d-34eba8517f1e · inbound

Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces cites this paper.

Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces Towards Understanding Sycophancy in Language Models

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-05-22T10:31:24.855785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d4c4c4eb-d159-49af-b47c-525369c7c370 · inbound

Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models cites this paper.

Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models Towards Understanding Sycophancy in Language Models

Reference 42

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T09:21:00.849707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 80b312db-b4a0-448d-b104-7aba98944dcd · inbound

Narrative over Numbers: The Identifiable Victim Effect and its Amplification Under Alignment and Reasoning in Large Language Models cites this paper.

Narrative over Numbers: The Identifiable Victim Effect and its Amplification Under Alignment and Reasoning in Large Language Models Towards Understanding Sycophancy in Language Models

Reference 19

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T10:56:06.024042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fafac062-eb0a-42f3-8512-5e00c33cfbfa · inbound

Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinions cites this paper.

Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinions Towards Understanding Sycophancy in Language Models

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-11T11:21:03.628157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9e10d53b-d2fb-4149-bac9-e7aa47795f4a · inbound

Gaslight, Gatekeep, V1-V3: Early Visual Cortex Alignment Shields Vision-Language Models from Sycophantic Manipulation cites this paper.

Gaslight, Gatekeep, V1-V3: Early Visual Cortex Alignment Shields Vision-Language Models from Sycophantic Manipulation Towards Understanding Sycophancy in Language Models

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f1e0b457-8a5d-445e-b644-b80927ac467c · inbound

Anthropomorphism and Trust in Human-Large Language Model interactions cites this paper.

Anthropomorphism and Trust in Human-Large Language Model interactions Towards Understanding Sycophancy in Language Models

Reference 35

Resolution: metadata mismatch; local_arxiv, observed 2026-05-15T17:46:23.858901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7f269f2d-527d-4e63-97c8-cbe6410b175a · inbound

How Robustly do LLMs Understand Execution Semantics? cites this paper.

How Robustly do LLMs Understand Execution Semantics? Towards Understanding Sycophancy in Language Models

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-05-15T19:46:33.609520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 368e4ec1-9fd3-48ae-ba0e-edcc6879929b · inbound

IACDM: Interactive Adversarial Convergence Development Methodology -- A Structured Framework for AI-Assisted Software Development cites this paper.

IACDM: Interactive Adversarial Convergence Development Methodology -- A Structured Framework for AI-Assisted Software Development Towards Understanding Sycophancy in Language Models

Reference 31

Resolution: metadata mismatch; local_arxiv, observed 2026-05-14T00:03:28.985652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 94bd0aa9-772e-46fc-9a2c-2a5b7bae2160 · inbound

Introspection Adapters: Training LLMs to Report Their Learned Behaviors cites this paper.

Introspection Adapters: Training LLMs to Report Their Learned Behaviors Towards Understanding Sycophancy in Language Models

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d7fd0975-c1f1-40b3-b453-8eb96578be2e · inbound

The Cognitive Penalty: Ablating System 1 and System 2 Reasoning in Edge-Native SLMs for Decentralized Consensus cites this paper.

The Cognitive Penalty: Ablating System 1 and System 2 Reasoning in Edge-Native SLMs for Decentralized Consensus Towards Understanding Sycophancy in Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation afa3076c-9c1c-48df-a0e2-bffdee48dba6 · inbound

Terminal Wrench: A Dataset of 331 Reward-Hackable Environments and 3,632 Exploit Trajectories cites this paper.

Terminal Wrench: A Dataset of 331 Reward-Hackable Environments and 3,632 Exploit Trajectories Towards Understanding Sycophancy in Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51f4bf77-3f7f-49b7-98ea-dd33e24ac9c9 · inbound

LLM-as-Judge Framework for Evaluating Tone-Induced Hallucination in Vision-Language Models cites this paper.

LLM-as-Judge Framework for Evaluating Tone-Induced Hallucination in Vision-Language Models Towards Understanding Sycophancy in Language Models

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation db8702a5-34e1-4156-9310-9973e2a199af · inbound

How Adversarial Environments Mislead Agentic AI? cites this paper.

How Adversarial Environments Mislead Agentic AI? Towards Understanding Sycophancy in Language Models

Reference 32

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T12:11:07.943414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0357dce7-c074-4ec2-92f8-e5d1fe5e9fd9 · inbound

The Rise of Verbal Tics in Large Language Models: A Systematic Analysis Across Frontier Models cites this paper.

The Rise of Verbal Tics in Large Language Models: A Systematic Analysis Across Frontier Models Towards Understanding Sycophancy in Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 06652c79-d9c0-4177-bd92-2f023eb5d49e · inbound

Pause or Fabricate? Training Language Models for Grounded Reasoning cites this paper.

Pause or Fabricate? Training Language Models for Grounded Reasoning Towards Understanding Sycophancy in Language Models

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-11T12:46:05.190917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 616817c7-8a79-40f1-b7b1-281dc89b3b70 · inbound

M-CARE: Standardized Clinical Case Reporting for AI Model Behavioral Disorders, with a 20-Case Atlas and Experimental Validation cites this paper.

M-CARE: Standardized Clinical Case Reporting for AI Model Behavioral Disorders, with a 20-Case Atlas and Experimental Validation Towards Understanding Sycophancy in Language Models

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-05-14T22:38:11.332230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a82001df-96a8-489f-8d12-01f8207c9fbb · inbound

Slot Machines: How LLMs Keep Track of Multiple Entities cites this paper.

Slot Machines: How LLMs Keep Track of Multiple Entities Towards Understanding Sycophancy in Language Models

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T14:01:04.052487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bd82c32c-ab5f-4c51-ba38-0597f5bc0a26 · inbound

Measuring Opinion Bias and Sycophancy via LLM-based Persuasion cites this paper.

Measuring Opinion Bias and Sycophancy via LLM-based Persuasion Towards Understanding Sycophancy in Language Models

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T14:26:04.278648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2acfdcf3-3023-4299-bcb6-51a7740ad6e8 · inbound

Peer Identity Bias in Multi-Agent LLM Evaluation: An Empirical Study Using the TRUST Democratic Discourse Analysis Pipeline cites this paper.

Peer Identity Bias in Multi-Agent LLM Evaluation: An Empirical Study Using the TRUST Democratic Discourse Analysis Pipeline Towards Understanding Sycophancy in Language Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-11T20:16:11.296085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 412de350-5dca-431c-abf1-e16aaa75dea6 · inbound

When AI reviews science: Can we trust the referee? cites this paper.

When AI reviews science: Can we trust the referee? Towards Understanding Sycophancy in Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5abd395a-d503-441c-9ca6-ea42d583a8af · inbound

Green Shielding: A User-Centric Approach Towards Trustworthy AI cites this paper.

Green Shielding: A User-Centric Approach Towards Trustworthy AI Towards Understanding Sycophancy in Language Models

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-11T21:56:24.178515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 88c45256-f80e-4cd0-adfe-482370cc707d · inbound

Preserving Disagreement: Architectural Heterogeneity and Coherence Validation in Multi-Agent Policy Simulation cites this paper.

Preserving Disagreement: Architectural Heterogeneity and Coherence Validation in Multi-Agent Policy Simulation Towards Understanding Sycophancy in Language Models

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-05-12T09:06:26.615855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 24aee952-ae3d-494a-911c-3ba0851d1e41 · inbound

The Impact of AI-Generated Text on the Internet cites this paper.

The Impact of AI-Generated Text on the Internet Towards Understanding Sycophancy in Language Models

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:29.613171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 860f4f54-7611-47a9-8155-51e8df1a07c4 · inbound

When Roles Fail: Epistemic Constraints on Advocate Role Fidelity in LLM-Based Political Statement Analysis cites this paper.

When Roles Fail: Epistemic Constraints on Advocate Role Fidelity in LLM-Based Political Statement Analysis Towards Understanding Sycophancy in Language Models

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:56:26.600289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 38010849-cd8e-45f3-af73-b71ebf64e3b8 · inbound

Political Bias Audits of LLMs Capture Sycophancy to the Inferred Auditor cites this paper.

Political Bias Audits of LLMs Capture Sycophancy to the Inferred Auditor Towards Understanding Sycophancy in Language Models

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-05-12T10:21:28.397042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 727d964d-9a83-4401-adf4-e0687ebd2a51 · inbound

The Cost of Consensus: Isolated Self-Correction Prevails Over Unguided Homogeneous Multi-Agent Debate cites this paper.

The Cost of Consensus: Isolated Self-Correction Prevails Over Unguided Homogeneous Multi-Agent Debate Towards Understanding Sycophancy in Language Models

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-11T15:16:10.814712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4041dacd-31f7-47a0-a8d6-4443a0c01524 · inbound

Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation cites this paper.

Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation Towards Understanding Sycophancy in Language Models

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:46:10.516783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.