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20242026
most citedRecDCL: Dual Contrastive Learning for Recommendation

61 citations · 82 across the 14 of their papers we have counts for

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Showing 2024 · cs.CLShow all

5 papers · 2 filters

cs.CL2024

BattleAgentBench: A Benchmark for Evaluating Cooperation and Competition Capabilities of Language Models in Multi-Agent Systems

Wei Wang, Dan Zhang, Tao Feng +2

Large Language Models (LLMs) are becoming increasingly powerful and capable of handling complex tasks, e.g., building single agents and multi-agent systems. Compared to single agen…

cs.CL2024★ 1 cited

Multi-turn Response Selection with Commonsense-enhanced Language Models

Yuandong Wang, Xuhui Ren, Tong Chen +3

As a branch of advanced artificial intelligence, dialogue systems are prospering. Multi-turn response selection is a general research problem in dialogue systems. With the assistan…

cs.CL2024★ 6 cited

ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

Dan Zhang, Sining Zhoubian, Ziniu Hu +3

Recent methodologies in LLM self-training mostly rely on LLM generating responses and filtering those with correct output answers as training data. This approach often yields a low…

cs.CL2024★ 2 cited

AutoRE: Document-Level Relation Extraction with Large Language Models

Lilong Xue, Dan Zhang, Yuxiao Dong +1

Large Language Models (LLMs) have demonstrated exceptional abilities in comprehending and generating text, motivating numerous researchers to utilize them for Information Extractio…

cs.CL2024★ 4 cited

SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models

Dan Zhang, Ziniu Hu, Sining Zhoubian +6

Large Language Models (LLMs) have shown promise in assisting scientific discovery. However, such applications are currently limited by LLMs' deficiencies in understanding intricate…