6 papers
Connect the Dots: Training LLMs for Long-Lifecycle Agents with Cross-Domain Generalization Via Reinforcement Learning
Yanxi Chen, Weijie Shi, Yuexiang Xie +4
This work presents a general framework for training large language models (LLMs) to "Connect the Dots" (CoD), a meta-capability required by long-lifecycle agents: as an LLM-based A…
Towards Advanced Mathematical Reasoning for LLMs via First-Order Logic Theorem Proving
Chuxue Cao, Mengze Li, Juntao Dai +7
Large language models (LLMs) have shown promising first-order logic (FOL) reasoning capabilities with applications in various areas. However, their effectiveness in complex mathema…
TCOD: Exploring Temporal Curriculum in On-Policy Distillation for Multi-turn Autonomous Agents
Jiaqi Wang, Wenhao Zhang, Weijie Shi +2
On-policy distillation (OPD) has shown strong potential for transferring reasoning ability from frontier or domain-specific models to smaller students. While effective on static si…
Perception, Understanding and Reasoning, A Multimodal Benchmark for Video Fake News Detection
Cui Yakun, Peng Qi, Fushuo Huo +6
The advent of multi-modal large language models (MLLMs) has greatly advanced research on video fake news detection (VFND) tasks. Existing benchmarks typically focus on the detectio…
Measuring Hong Kong Massive Multi-Task Language Understanding
Chuxue Cao, Zhenghao Zhu, Junqi Zhu +6
Multilingual understanding is crucial for the cross-cultural applicability of Large Language Models (LLMs). However, evaluation benchmarks designed for Hong Kong's unique linguisti…
AgentMonitor: A Plug-and-Play Framework for Predictive and Secure Multi-Agent Systems
Chi-Min Chan, Jianxuan Yu, Weize Chen +6
The rapid advancement of large language models (LLMs) has led to the rise of LLM-based agents. Recent research shows that multi-agent systems (MAS), where each agent plays a specif…