10 papers
Auto-FlexSwitch: Efficient Dynamic Model Merging via Learnable Task Vector Compression
Junqi Gao, Dazhi Zhang, Zhichang Guo +3
Model merging has attracted attention as an effective path toward multi-task adaptation by integrating knowledge from multiple task-specific models. Among existing approaches, dyna…
WIST: Web-Grounded Iterative Self-Play Tree for Domain-Targeted Reasoning Improvement
Fangyuan Li, Pengfei Li, Shijie Wang +4
Recent progress in reinforcement learning with verifiable rewards (RLVR) offers a practical path to self-improvement of language models, but existing methods face a key trade-off:…
MARTI-MARS: Scaling Multi-Agent Self-Search via Reinforcement Learning for Code Generation
Shijie Wang, Pengfei Li, Yikun Fu +21
While the complex reasoning capability of Large Language Models (LLMs) has attracted significant attention, single-agent systems often encounter inherent performance ceilings in co…
PDAC: Efficient Coreset Selection for Continual Learning via Probability Density Awareness
Junqi Gao, Zhichang Guo, Dazhi Zhang +3
Rehearsal-based Continual Learning (CL) maintains a limited memory buffer to store replay samples for knowledge retention, making these approaches heavily reliant on the quality of…
Bohdi: Heterogeneous LLM Fusion with Automatic Data Exploration
Junqi Gao, Zhichang Guo, Dazhi Zhang +5
Heterogeneous Large Language Model (LLM) fusion integrates the strengths of multiple source LLMs with different architectures into a target LLM with low computational overhead. Whi…
A Survey of Reinforcement Learning for Large Reasoning Models
Kaiyan Zhang, Yuxin Zuo, Bingxiang He +36
In this paper, we survey recent advances in Reinforcement Learning (RL) for reasoning with Large Language Models (LLMs). RL has achieved remarkable success in advancing the frontie…