Paper Citation Record · LEDGER

Feedback Loops With Language Models Drive In-Context Reward Hacking

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2402.06627.

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

pith.paper-citation-record.v1
2402.06627 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:57:23.024600Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T18:44:28.860347Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d582b9b6-d5ed-4597-91f2-37a359ee5adf · inbound

LLM Evaluators Recognize and Favor Their Own Generations cites this paper.

LLM Evaluators Recognize and Favor Their Own Generations Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-22T18:44:28.862606Z

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 bccdd9df-c831-448e-9f5d-c3cdee503a35 · inbound

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

Thinking beyond the anthropomorphic paradigm benefits LLM research Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T22:21:52.673974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e905d17-97ac-4822-9855-bdfcdb3f7df4 · inbound

VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model cites this paper.

VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:13:57.461019Z

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 fee8b775-2e71-4ce1-b46f-f555e57a8170 · inbound

Exploring the Secondary Risks of Large Language Models cites this paper.

Exploring the Secondary Risks of Large Language Models Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:42:13.928654Z

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 5fc8f8d2-3bc5-4065-acc1-1db253b092fd · inbound

Causal Reward Adjustment: Mitigating Reward Hacking in External Reasoning via Backdoor Correction cites this paper.

Causal Reward Adjustment: Mitigating Reward Hacking in External Reasoning via Backdoor Correction Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T00:49:56.840261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca149062-f3c4-4f18-b192-c05c9a81c0c0 · inbound

Thinking-Based Non-Thinking: Solving the Reward Hacking Problem in Training Hybrid Reasoning Models via Reinforcement Learning cites this paper.

Thinking-Based Non-Thinking: Solving the Reward Hacking Problem in Training Hybrid Reasoning Models via Reinforcement Learning Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T11:57:55.899447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 636169a7-8160-490b-a12f-060c26b31b6e · 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 Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T20:33:14.744513Z

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 207b8bc6-e046-4d22-848b-aea22f51b712 · inbound

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges cites this paper.

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:00:28.675549Z

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 ffc46a41-e1c3-40a8-a160-731b1f3714e3 · inbound

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack cites this paper.

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:32:56.960515Z

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 a3e2b4bd-a5c3-4839-b964-10383a8d73ad · inbound

Diagnosing Training Inference Mismatch in LLM Reinforcement Learning cites this paper.

Diagnosing Training Inference Mismatch in LLM Reinforcement Learning Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T02:08:29.456354Z

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 32f7e0b6-64ed-438b-af0e-fe9c6e80c8c2 · inbound

Do Modules Stay in Their Lane? Role Drift in Compound LLM Systems cites this paper.

Do Modules Stay in Their Lane? Role Drift in Compound LLM Systems Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T08:17:25.689409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 832076a7-7b7e-4022-951a-a04f9ca0be32 · inbound

From Sports to Safety: Benchmarking Proactive Risk Inference in MLLMs cites this paper.

From Sports to Safety: Benchmarking Proactive Risk Inference in MLLMs Feedback Loops With Language Models Drive In-Context Reward Hacking

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-08T10:57:23.024600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.