7 citations · 12 across the 20 of their papers we have counts for
6 papers · 1 filter
Thought-Retriever: Don't Just Retrieve Raw Data, Retrieve Thoughts for Memory-Augmented Agentic Systems
Tao Feng, Pengrui Han, Guanyu Lin +2
Large language models (LLMs) have transformed AI research thanks to their powerful internal capabilities and knowledge. However, existing LLMs still fail to effectively incorporate…
Router-R1: Teaching LLMs Multi-Round Routing and Aggregation via Reinforcement Learning
Haozhen Zhang, Tao Feng, Jiaxuan You
The rapid emergence of diverse large language models (LLMs) has spurred the development of LLM routers that assign user queries to the most suitable model. However, existing LLM ro…
ResearchTown: Simulator of Human Research Community
Haofei Yu, Zhaochen Hong, Zirui Cheng +5
Large Language Models (LLMs) have demonstrated remarkable potential in scientific domains, yet a fundamental question remains unanswered: Can we simulate human research communities…
Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs
Haozhen Zhang, Tao Feng, Jiaxuan You
Retrieval-augmented generation (RAG) has revitalized Large Language Models (LLMs) by injecting non-parametric factual knowledge. Compared with long-context LLMs, RAG is considered…
Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized Academic Assistance
Guanyu Lin, Tao Feng, Pengrui Han +2
As scientific research proliferates, researchers face the daunting task of navigating and reading vast amounts of literature. Existing solutions, such as document QA, fail to provi…
CITING: Large Language Models Create Curriculum for Instruction Tuning
Tao Feng, Zifeng Wang, Jimeng Sun
The recent advancement of large language models (LLMs) has been achieved through a combo of instruction tuning and human alignment. However, building manually crafted instruction d…