9 papers
World Models as Adversaries: Multi-Agent Self-Play Fine-Tuning for Robust Motion Planning
Tong Nie, Yuewen Mei, Junlin He +3
Robust motion planning in dense traffic requires autonomous vehicles to interact in rare and safety-critical scenarios that are underrepresented in naturalistic driving data. Altho…
LLMSynthor: Macro-Aligned Micro-Records Synthesis with Large Language Models
Yihong Tang, Menglin Kong, Junlin He +3
Macro-aligned micro-records are crucial for credible simulations in social science and urban studies. For example, epidemic models are only reliable when individual-level mobility…
Reasoning-preserved Efficient Distillation of Large Language Models via Activation-aware Initialization
Junlin He, Yihong Tang, Tong Nie +5
Efficient Distillation (EDistill) compresses large language models (LLMs) by structured pruning parameters and tuning lightweight modules with high training efficiency. Although th…
Dr-CiK: A Testbed for Foresight-Driven Agents
Yihong Tang, Andrew Robert Williams, Arjun Ashok +6
Time series forecasting in real-world settings often depends not only on historical observations, but also on external context that must be actively discovered from noisy, heteroge…
CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents
Yihong Tang, Kehai Chen, Liang Yue +2
Recent advancements in Reinforcement Learning (RL), particularly Group Relative Policy Optimization (GRPO), have significantly enhanced the reasoning capabilities of Large Language…
Bridge: Retrieval-Augmented Spatiotemporal Modeling for Urban Delivery Demand
Yihong Tang, Tong Nie, Junlin He +3
Forecasting urban delivery demand becomes substantially more challenging when newly added service regions lack historical records. Existing spatiotemporal forecasters effectively m…