activity
20232026
most citedThe Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism

7 citations · 16 across the 19 of their papers we have counts for

collaborators
Showing 2024Show all

10 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.CV2024★ 2 cited

VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models

Lei Li, Yuancheng Wei, Zhihui Xie +9

Vision-language generative reward models (VL-GenRMs) play a crucial role in aligning and evaluating multimodal AI systems, yet their own evaluation remains under-explored. Current…

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★ 7 cited

The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism

Yifan Song, Guoyin Wang, Sujian Li +1

Current evaluations of large language models (LLMs) often overlook non-determinism, typically focusing on a single output per example. This limits our understanding of LLM performa…

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

Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement

Weimin Xiong, Yifan Song, Xiutian Zhao +6

Large language model agents have exhibited exceptional performance across a range of complex interactive tasks. Recent approaches have utilized tuning with expert trajectories to e…

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★ 2 cited

Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents

Yifan Song, Da Yin, Xiang Yue +3

Large Language Models (LLMs) have become integral components in various autonomous agent systems. In this study, we present an exploration-based trajectory optimization approach, r…