3 citations · 6 across the 9 of their papers we have counts for
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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.AI2025
Confidence as a Reward: Transforming LLMs into Reward Models
He Du, Bowen Li, Chengxing Xie +3
Reward models can significantly enhance the reasoning capabilities of large language models (LLMs), but they typically require extensive curated data and costly training. To mitiga…
cs.AI2024★ 3 cited
A Human-Like Reasoning Framework for Multi-Phases Planning Task with Large Language Models
Chengxing Xie, Difan Zou
Recent studies have highlighted their proficiency in some simple tasks like writing and coding through various reasoning strategies. However, LLM agents still struggle with tasks t…