6 citations · 8 across the 8 of their papers we have counts for
8 papers
Early Diagnosis of Wasted Computation in Multi-Agent LLM Systems via Failure-Aware Observability
Xianyou Li, Weiran Yan, Yichao Wu +4
Failure-aware observability diagnoses wasted computation in multi-agent LLM systems before final-answer evaluation can explain what went wrong. We propose a trace-based framework f…
Recursive Multi-Agent Trading System: Iterative Optimized Portfolio Strategy Under Geopolitical Uncertainty
Jing Yang, Yichao Wu, Jianan Liu +4
Recursive Multi-Agent Trading System (RMATS) integrates four specialized agents -- Sentiment, Report, Analysis, and Risk -- coordinated through a recursive Manager Agent with itera…
TA-Mem: Tool-Augmented Autonomous Memory Retrieval for LLM in Long-Term Conversational QA
Mengwei Yuan, Jianan Liu, Jing Yang +4
Large Language Model (LLM) has exhibited strong reasoning ability in text-based contexts across various domains, yet the limitation of context window poses challenges for the model…
Tiny-Critic RAG: Empowering Agentic Fallback with Parameter-Efficient Small Language Models
Yichao Wu, Penghao Liang, Yafei Xiang +5
Retrieval-Augmented Generation (RAG) grounds Large Language Models (LLMs) to mitigate factual hallucinations. Recent paradigms shift from static pipelines to Modular and Agentic RA…
DynaRAG: Bridging Static and Dynamic Knowledge in Retrieval-Augmented Generation
Penghao Liang, Mengwei Yuan, Jianan Liu +4
We present DynaRAG, a retrieval-augmented generation (RAG) framework designed to handle both static and time-sensitive information needs through dynamic knowledge integration. Unli…
Maximizing User Experience with LLMOps-Driven Personalized Recommendation Systems
Chenxi Shi, Penghao Liang, Yichao Wu +2
The integration of LLMOps into personalized recommendation systems marks a significant advancement in managing LLM-driven applications. This innovation presents both opportunities…
Research on the Application of Deep Learning-based BERT Model in Sentiment Analysis
Yichao Wu, Zhengyu Jin, Chenxi Shi +2
This paper explores the application of deep learning techniques, particularly focusing on BERT models, in sentiment analysis. It begins by introducing the fundamental concept of se…
Emerging Synergies Between Large Language Models and Machine Learning in Ecommerce Recommendations
Xiaonan Xu, Yichao Wu, Penghao Liang +2
With the boom of e-commerce and web applications, recommender systems have become an important part of our daily lives, providing personalized recommendations based on the user's p…