Google's Thinking-in-Bets Nearly Eliminates False Reversals in LLM Agents
google · hf · 2026-10-27
A training-free method from Google researcher Nghi D. Q. Bui tackles sycophancy: before reading user feedback, the agent privately records its main claims, the checks supporting them, and its confidence. When challenged, it consults this Claim Checklist to keep verified work intact while investigating only uncertain parts.
- Evaluated on five Gemini models (3.5 Flash-Lite through 4.0 Argon) across eight benchmarks including SWE-Together, DeepSWE, SycEval, and Terminal-Bench.
- Recording claims before criticism nearly eliminates false reversals in patch review and protects passing report drafts under mistaken pushback; writing the same record after reading the complaint recovers little of the gain. In multi-turn coding, it substantially reduces unnecessary file edits after mistaken complaints.
More from coding & agent
- Claude and Codex go multiplayer: coding agents join Zoom/Meet calls with vision via Tana — Scobleizer · 2026-10-27
- OpenAI, Anthropic, Alibaba, Hugging Face donate agent stack pieces to one open foundation — YvesMulkers · 2026-10-27
- DevSpeak MCP lets your coding agent polish PR descriptions and commit messages — modelcontextprotocol · 2026-10-27
- ThreadMind MCP gives AI agents a Git-like memory tree to cut token costs — mahmu_tech · 2026-10-27
- He let Claude design a complete e-ink business card, from schematic to product page — isaul32 · 2026-10-27
- Papers with Code revives as an Apache 2.0 open-source project with public API and MCP server — NielsRogge · 2026-10-27