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20212025
most citedFaithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods

28 citations · 34 across the 8 of their papers we have counts for

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12 papers · 1 filter

cs.CL2025

Chain-of-Thought Matters: Improving Long-Context Language Models with Reasoning Path Supervision

Dawei Zhu, Xiyu Wei, Guangxiang Zhao +7

Recent advances in Large Language Models (LLMs) have highlighted the challenge of handling long-context tasks, where models need to reason over extensive input contexts to aggregat…

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

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

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…