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20212026
most citedLarge Language Models are not Fair Evaluators

33 citations · 77 across the 29 of their papers we have counts for

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7 papers · 1 filter

cs.CL2024

More Tokens, Lower Precision: Towards the Optimal Token-Precision Trade-off in KV Cache Compression

Jiebin Zhang, Dawei Zhu, Yifan Song +6

As large language models (LLMs) process increasing context windows, the memory usage of KV cache has become a critical bottleneck during inference. The mainstream KV compression me…

cs.CL2024

AgentBank: Towards Generalized LLM Agents via Fine-Tuning on 50000+ Interaction Trajectories

Yifan Song, Weimin Xiong, Xiutian Zhao +6

Fine-tuning on agent-environment interaction trajectory data holds significant promise for surfacing generalized agent capabilities in open-source large language models (LLMs). In…

cs.CL2024

EERPD: Leveraging Emotion and Emotion Regulation for Improving Personality Detection

Zheng Li, Dawei Zhu, Qilong Ma +2

Personality is a fundamental construct in psychology, reflecting an individual's behavior, thinking, and emotional patterns. Previous researches have made some progress in personal…

cs.CL2024

Long Context Alignment with Short Instructions and Synthesized Positions

Wenhao Wu, Yizhong Wang, Yao Fu +3

Effectively handling instructions with extremely long context remains a challenge for Large Language Models (LLMs), typically necessitating high-quality long data and substantial c…

cs.CL2024★ 1 cited

LongEmbed: Extending Embedding Models for Long Context Retrieval

Dawei Zhu, Liang Wang, Nan Yang +4

Embedding models play a pivot role in modern NLP applications such as IR and RAG. While the context limit of LLMs has been pushed beyond 1 million tokens, embedding models are stil…

cs.CL2024

CoUDA: Coherence Evaluation via Unified Data Augmentation

Dawei Zhu, Wenhao Wu, Yifan Song +3

Coherence evaluation aims to assess the organization and structure of a discourse, which remains challenging even in the era of large language models. Due to the scarcity of annota…

cs.CL2024

WIKIGENBENCH: Exploring Full-length Wikipedia Generation under Real-World Scenario

Jiebin Zhang, Eugene J. Yu, Qinyu Chen +8

It presents significant challenges to generate comprehensive and accurate Wikipedia articles for newly emerging events under a real-world scenario. Existing attempts fall short eit…