9 papers · 1 filter
Trace-Based On-Policy Distillation for Masked Diffusion Language Models
Haolin Ren, Ziyang Huang, Chenhao Yuan +2
Diffusion large language models (dLLMs) are a promising alternative to autoregressive generation. However, reasoning-oriented post-training for dLLMs remains challenging. Supervise…
Break Through the Compression Bottleneck: From Theory to Practice
Xiusheng Huang, Lu Wang, Yequan Wang +2
As the parameter size of language models continues to grow, effective model compression is required to reduce their computational and memory overhead. Existing compression methods…
DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios
Jinxiang Meng, Shaoping Huang, Fangyu Lei +17
Real-world data visualization (DV) requires native environmental grounding, cross-platform evolution, and proactive intent alignment. Yet, existing benchmarks often suffer from cod…
InfoFlow: Reinforcing Search Agent Via Reward Density Optimization
Kun Luo, Hongjin Qian, Zheng Liu +5
Reinforcement Learning with Verifiable Rewards (RLVR) is a promising approach for enhancing agentic deep search. However, its application is often hindered by low \textbf{Reward De…
Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate
Ziyang Huang, Wangtao Sun, Jun Zhao +1
This paper systematically addresses the challenges of rule retrieval, a crucial yet underexplored area. Vanilla retrieval methods using sparse or dense retrievers to directly searc…
Reinforced Internal-External Knowledge Synergistic Reasoning for Efficient Adaptive Search Agent
Ziyang Huang, Xiaowei Yuan, Yiming Ju +2
Retrieval-augmented generation (RAG) is a common strategy to reduce hallucinations in Large Language Models (LLMs). While reinforcement learning (RL) can enable LLMs to act as sear…