6 papers
ConSteer-RL: Steering Reasoning Capabilities in Large Language Models via Confidence-Aware Reinforcement Learning
Qing Miao, Yiming Zhao, Jing Yang +5
Reinforcement Learning from Verifiable Rewards (RLVR) has recently become a key paradigm for improving the reasoning abilities of Large Language Models (LLMs), yet it remains limit…
CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models
Fengze Yang, Bo Yu, Xuewen Luo +2
Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods theoretically save FLOPs, post-…
Adaptive Stopping for Multi-Turn LLM Reasoning
Xiaofan Zhou, Huy Nguyen, Bo Yu +2
Large Language Models (LLMs) increasingly rely on multi-turn reasoning and interaction, such as adaptive retrieval-augmented generation (RAG) and ReAct-style agents, to answer diff…
Locatability-Guided Adaptive Reasoning for Image Geo-Localization with Vision-Language Models
Bo Yu, Fengze Yang, Yiming Liu +6
The emergence of Vision-Language Models (VLMs) has introduced new paradigms for global image geo-localization through retrieval-augmented generation (RAG) and reasoning-driven infe…
Independent Mobility GPT (IDM-GPT): A Self-Supervised Multi-Agent Large Language Model Framework for Customized Traffic Mobility Analysis Using Machine Learning Models
Fengze Yang, Xiaoyue Cathy Liu, Lingjiu Lu +2
With the urbanization process, an increasing number of sensors are being deployed in transportation systems, leading to an explosion of big data. To harness the power of this vast…
SenseRAG: Constructing Environmental Knowledge Bases with Proactive Querying for LLM-Based Autonomous Driving
Xuewen Luo, Fan Ding, Fengze Yang +4
This study addresses the critical need for enhanced situational awareness in autonomous driving (AD) by leveraging the contextual reasoning capabilities of large language models (L…