6 papers
MARS: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation
Pengfei Li, Shijie Wang, Fangyuan Li +7
Reinforcement learning (RL) paradigms have demonstrated strong performance on reasoning-intensive tasks such as code generation. However, limited trajectory diversity often leads t…
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…
Leveraging Adaptive Group Negotiation for Heterogeneous Multi-Robot Collaboration with Large Language Models
Siqi Song, Xuanbing Xie, Zonglin Li +3
Multi-robot collaboration tasks often require heterogeneous robots to work together over long horizons under spatial constraints and environmental uncertainties. Although Large Lan…
Sequential Diffusion Language Models
Yangzhou Liu, Yue Cao, Hao Li +13
Diffusion language models (DLMs) have strong theoretical efficiency but are limited by fixed-length decoding and incompatibility with key-value (KV) caches. Block diffusion mitigat…
Intern-S1: A Scientific Multimodal Foundation Model
Lei Bai, Zhongrui Cai, Yuhang Cao +173
In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…