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20212026
most citedDeep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey

7 citations · 12 across the 20 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CL2024★ 1 cited

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…

cs.CL2024

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…

cs.AI2024

GraphRouter: A Graph-based Router for LLM Selections

Tao Feng, Yanzhen Shen, Jiaxuan You

The rapidly growing number and variety of Large Language Models (LLMs) present significant challenges in efficiently selecting the appropriate LLM for a given query, especially con…

cs.CL2024

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…

cs.CE2024

Deep Reinforcement Learning for Modelling Protein Complexes

Ziqi Gao, Tao Feng, Jiaxuan You +4

AlphaFold can be used for both single-chain and multi-chain protein structure prediction, while the latter becomes extremely challenging as the number of chains increases. In this…

cs.AI2024★ 1 cited

How Far Are We From AGI: Are LLMs All We Need?

Tao Feng, Chuanyang Jin, Jingyu Liu +5

The evolution of artificial intelligence (AI) has profoundly impacted human society, driving significant advancements in multiple sectors. AGI, distinguished by its ability to exec…