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20242026
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cs.AI2026

Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling

Yafu Li, Runzhe Zhan, Haoran Zhang +25

Recent progress in reasoning models has substantially advanced long-horizon mathematical and scientific problem solving, with several systems now reaching gold-medal-level performa…

cs.AI2026

P1-VL: Bridging Visual Perception and Scientific Reasoning in Physics Olympiads

Yun Luo, Futing Wang, Qianjia Cheng +28

The transition from symbolic manipulation to science-grade reasoning represents a pivotal frontier for Large Language Models (LLMs), with physics serving as the critical test ancho…

cs.AI2026

Teaching Large Reasoning Models Effective Reflection

Hanbin Wang, Jingwei Song, Jinpeng Li +5

Large Reasoning Models (LRMs) have recently shown impressive performance on complex reasoning tasks, often by engaging in self-reflective behaviors such as self-critique and backtr…

cs.AI2025

From and to : LLMs Learn New Skills in RL by Composing Old Ones

Lifan Yuan, Weize Chen, Yuchen Zhang +7

Does RL teach LLMs genuinely new skills, or does it merely activate existing ones? This question lies at the core of ongoing debates about the role of RL in LLM post-training. On o…

cs.AI2025

PhysicsMinions: Winning Gold Medals in the Latest Physics Olympiads with a Coevolutionary Multimodal Multi-Agent System

Fangchen Yu, Junchi Yao, Ziyi Wang +10

Physics is central to understanding and shaping the real world, and the ability to solve physics problems is a key indicator of real-world physical intelligence. Physics Olympiads,…

cs.AI2025

SCI-Verifier: Scientific Verifier with Thinking

Shenghe Zheng, Chenyu Huang, Fangchen Yu +8

As large language models (LLMs) are increasingly applied to scientific reasoning, the complexity of answer formats and the diversity of equivalent expressions make answer verificat…