9 papers
Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning
Zhitian Hou, Yuhang Liu, Pengkai Wang +8
Applying a valid medication-safety rule when its patient-specific conditions are not met can produce an incorrect decision. Existing medical evaluations largely use isolated and fi…
InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training
Pengkai Wang, Pengwei Liu, Qi Zuo +3
Reinforcement learning (RL) has powered many recent breakthroughs in large language models (LLMs), especially for tasks where rewards can be computed automatically, such as code ge…
Model Merging Scaling Laws in Large Language Models
Yuanyi Wang, Yanggan Gu, Yiming Zhang +6
We study empirical scaling laws for language model merging measured by cross-entropy. Despite its wide practical use, merging lacks a quantitative rule that predicts returns as we…
Quantization Meets Reasoning: Exploring and Mitigating Degradation of Low-Bit LLMs in Mathematical Reasoning
Zhen Li, Yupeng Su, Songmiao Wang +8
Low-bit post-training quantization (PTQ) is a practical route to deploy reasoning-capable LLMs under tight memory and latency budgets, yet it can markedly impair mathematical reaso…
InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimization
Yuhang Liu, Zeyu Liu, Shuanghe Zhu +10
The emergence of Multimodal Large Language Models (MLLMs) has propelled the development of autonomous agents that operate on Graphical User Interfaces (GUIs) using pure visual inpu…
A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models
Wenjun Wang, Shuo Cai, Congkai Xie +7
The immense computational cost of training Large Language Models (LLMs) presents a major barrier to innovation. While FP8 training offers a promising solution with significant theo…