7 papers
GRAPHIA: Harnessing Social Graph Data to Enhance LLM-Based Social Simulation
Jiarui Ji, Zehua Zhang, Zhewei Wei +3
Large language models (LLMs) have shown promise in simulating human-like social behaviors. Social graphs provide high-quality supervision signals that encode both local interaction…
BARD: budget-aware reasoning distillation
Lujie Niu, Lei Shen, Yi Jiang +4
While long Chain-of-Thought (CoT) distillation effectively transfers reasoning capability to smaller language models, the reasoning process often remains redundant and computationa…
Reasoning Palette: Modulating Reasoning via Latent Contextualization for Controllable Exploration for (V)LMs
Rujiao Long, Yang Li, Xingyao Zhang +7
Exploration capacity shapes both inference-time performance and reinforcement learning (RL) training for large (vision-) language models, as stochastic sampling often yields redund…
SocialDriveGen: Generating Diverse Traffic Scenarios with Controllable Social Interactions
Jiaguo Tian, Zhengbang Zhu, Shenyu Zhang +6
The generation of realistic and diverse traffic scenarios in simulation is essential for developing and evaluating autonomous driving systems. However, most simulation frameworks r…
RAVR: Reference-Answer-guided Variational Reasoning for Large Language Models
Tianqianjin Lin, Xi Zhao, Xingyao Zhang +5
Reinforcement learning (RL) can refine the reasoning abilities of large language models (LLMs), but critically depends on a key prerequisite: the LLM can already generate high-util…
QAgent: A modular Search Agent with Interactive Query Understanding
Yi Jiang, Lei Shen, Lujie Niu +3
Large language models (LLMs) excel at natural language tasks but are limited by their static parametric knowledge, especially in knowledge-intensive task. Retrieval-augmented gener…