arXiv 2610.21204 · cs.AI · 2026-10-15
Entertain, then Cancel: How Thinking Makes Reasoning Models Read Some and Or Literally
Zhizhuo Kou, Jian Yang, Pengfei Hao, Junyu Luo, Jingshu Peng, Sirui Han, Yike Guo
The Hong Kong University of Science and Technology
In latest · #367 Added on 2026-10-25
One-line takeaway
Thinking longer makes reasoning models (GPT-5 included) read 'some' and 'or' literally, cancelling everyday implicatures; traces show models first entertain the enriched reading then cancel it, and answering from the early reading recovers it.
研究发现推理模型想得越多,越把 some、or 读成纯逻辑义,丢掉“不是全部”“不是两者都”的日常含义,GPT-5 也一样;轨迹显示模型先想到含义再推翻,用早期读法作答可挽回。
Read on arXiv PDF Hugging Face discussion Code
Topics & disciplines
More on Reasoning
- LEV: Thinking Fast and Deep with Looped Decision Models ▲337
- Thinking Inertia: LLMs Keep Thinking When Told Not To ▲241
- Rethinking Latent Visual Reasoning: Grounding Latent Reasoning in Visual Evidence ▲224
- Questioning the Questions: Sustaining Self-Evolution in Reasoning Models ▲85
- Improving Test-Time Scaling with Adaptive Looped Transformers ▲62
More on LLMs
- Jeva: System One Models from First Principles 2026-10-13 · ▲371
- Post-Training Leaves Behavioral Shadows on Unrelated Decisions 2026-09-24 · ▲273
- WeVisOne-VL: Unified Visual Perception from Objects to Pixels 2026-10-22 · ▲247
- OmniEdu: Open Foundation Models for Learning and Teaching 2026-09-19 · ▲240
- SpatialScout: Can VLM Agents Actively Explore and Map 3D Scenes? 2026-10-19 · ▲170
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-26.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.