5 papers
OpenPM: Auditable Point-in-Time Evaluation for LLM Portfolio-Management Agents
Xinying Cai, Minghao Guo, Jiahe Liu +7
Large language models are increasingly used to read markets, assess risk, and allocate capital. However, reported results for LLM trading agents can be inflated by look-ahead leaka…
Skill-RAG: Failure-State-Aware Retrieval Augmentation via Hidden-State Probing and Skill Routing
Kai Wei, Raymond Li, Xi Zhu +4
Retrieval-Augmented Generation (RAG) has emerged as a foundational paradigm for grounding large language models in external knowledge. While adaptive retrieval mechanisms have impr…
AEL: Agent Evolving Learning for Open-Ended Environments
Wujiang Xu, Jiaojiao Han, Minghao Guo +4
LLM agents increasingly operate in open-ended environments spanning hundreds of sequential episodes, yet they remain largely stateless: each task is solved from scratch without con…
SAGE: An Agentic Explainer Framework for Interpreting SAE Features in Language Models
Jiaojiao Han, Wujiang Xu, Mingyu Jin +1
Large language models (LLMs) have achieved remarkable progress, yet their internal mechanisms remain largely opaque, posing a significant challenge to their safe and reliable deplo…
SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
Wujiang Xu, Qitian Wu, Zujie Liang +5
Sequential Recommendation (SR) task involves predicting the next item a user is likely to interact with, given their past interactions. The SR models examine the sequence of a user…