13 papers
Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing
Yutong Yin, Mingyu Jin, Jin Pan +12
Test-time scaling improves language-model reasoning, but existing approaches often face a difficult trade-off: long chain-of-thought sampling remains single-threaded, while sentenc…
IAPO: Input Attribution-Aware Policy Optimization for Tool Use in Small Multimodal Agents
Yifan Yang, Zhen Zhang, Jiayi Tian +2
This paper investigates reinforcement learning (RL) methods for improving tool-calling capabilities in multimodal small language model (SLM) agents. While existing works have explo…
Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling
Zhen Zhang, Changyi Yang, Zijie Xia +11
Tokens are the fundamental units of computation in modern autoregressive models, and generation length directly influences both inference cost and reasoning performance. Despite it…
When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation
Henry Peng Zou, Chunyu Miao, Wei-Chieh Huang +16
As LLM agents transition from short, static problem solving to executing complex, long-horizon tasks in dynamic environments, the ability to handle user interruptions, such as addi…
MathGen: Revealing the Illusion of Mathematical Competence through Text-to-Image Generation
Ruiyao Liu, Hui Shen, Ping Zhang +16
Modern generative models have demonstrated the ability to solve challenging mathematical problems. In many real-world settings, however, mathematical solutions must be expressed vi…
CM2: Reinforcement Learning with Checklist Rewards for Multi-Turn and Multi-Step Agentic Tool Use
Zhen Zhang, Kaiqiang Song, Xun Wang +11
AI agents are increasingly used to solve real-world tasks by reasoning over multi-turn user interactions and invoking external tools. However, applying reinforcement learning to su…