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R0040/2026-04-01/Q002/S02
Research R0040 — RLHF Alternatives
Run 2026-04-01
Query Q002
Search S02

WebSearch — Reward shaping and sycophancy mitigation within RLHF

Summary

Field Value
Source/Database WebSearch
Query terms "reward shaping" "reward correction" sycophancy mitigation RLHF training intervention 2025 2026
Filters None
Results returned 10
Results selected 3
Results rejected 7

Selected Results

Result Title URL Rationale
S02-R01 Reward Shaping to Mitigate Reward Hacking in RLHF https://arxiv.org/abs/2502.18770 Directly addresses reward shaping as RLHF mitigation
S02-R02 How RLHF Amplifies Sycophancy (Benade PDF) https://www.gerdusbenade.com/files/26_sycophancy.pdf Proposed reward correction targeting sycophancy amplification
S02-R03 One Bias After Another: Mechanistic Reward Shaping https://arxiv.org/html/2603.03291 Analysis of persistent biases in language reward models

Rejected Results

Result Title URL Rationale
S02-R04 Reward Hacking in RL (Lil'Log) https://lilianweng.github.io/posts/2024-11-28-reward-hacking/ General reward hacking overview, not sycophancy-specific
S02-R05 Reward Shaping OpenReview PDF https://openreview.net/pdf?id=62A4d5Mokc Same paper as R01, different format
S02-R06 Reward Shaping ResearchGate https://www.researchgate.net/publication/389392526_Reward_Shaping_to_Mitigate_Reward_Hacking_in_RLHF Same paper as R01, different platform
S02-R07 Reward Hacking Defense Rubric https://www.emergentmind.com/topics/reward-hacking-defense-rubric Aggregator topic page
S02-R08 Natural Emergent Misalignment (Anthropic) https://assets.anthropic.com/m/74342f2c96095771/original/Natural-emergent-misalignment-from-reward-hacking-paper.pdf Focuses on emergent misalignment, tangential to sycophancy
S02-R09 Sycophancy Whitepaper https://jinaldesai.com/wp-content/uploads/2026/02/AI_Sycophancy_Whitepaper_JinalDesai.pdf Duplicate from S01, non-peer-reviewed
S02-R10 Reward Shaping arXiv PDF https://arxiv.org/pdf/2502.18770 Same paper as R01, PDF format

Notes

Reward shaping within RLHF is an active research area. The PAR method (Fu et al.) and Shapira et al.'s agreement penalty represent two distinct approaches to mitigating sycophancy without abandoning RLHF.