6 papers
Canonical Intermediate Representation for LLM-based optimization problem formulation and code generation
Zhongyuan Lyu, Shuoyu Hu, Lujie Liu +2
Automatically formulating optimization models from natural language descriptions is a growing focus in operations research, yet current LLM-based approaches struggle with the compo…
ToolTok: Tool Tokenization for Efficient and Generalizable GUI Agents
Xiaoce Wang, Guibin Zhang, Junzhe Li +3
Existing GUI agent models relying on coordinate-based one-step visual grounding struggle with generalizing to varying input resolutions and aspect ratios. Alternatives introduce co…
InfiAgent: An Infinite-Horizon Framework for General-Purpose Autonomous Agents
Chenglin Yu, Yuchen Wang, Songmiao Wang +2
LLM agents can reason and use tools, but they often break down on long-horizon tasks due to unbounded context growth and accumulated errors. Common remedies such as context compres…
InfiAgent: Self-Evolving Pyramid Agent Framework for Infinite Scenarios
Chenglin Yu, Yang Yu, Songmiao Wang +5
Large Language Model (LLM) agents have demonstrated remarkable capabilities in organizing and executing complex tasks, and many such agents are now widely used in various applicati…
InfiMed: Low-Resource Medical MLLMs with Advancing Understanding and Reasoning
Zeyu Liu, Zhitian Hou, Guanghao Zhu +3
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in domains such as visual understanding and mathematical reasoning. However, their application in the med…
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…