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20242026
most citedA Comparative Study of Quality Evaluation Methods for Text Summarization

6 citations · 11 across the 9 of their papers we have counts for

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cs.CL2026

LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation

Huyen Nguyen, Haoxuan Zhang, Yang Zhang +2

Reliable evaluation of large language model (LLM)-generated summaries remains an open challenge, particularly across heterogeneous domains and document lengths. We conduct a compre…

cs.CL2026

LongSumEval: Question-Answering Based Evaluation and Feedback-Driven Refinement for Long Document Summarization

Huyen Nguyen, Haoxuan Zhang, Yang Zhang +2

Evaluating long document summaries remains the primary bottleneck in summarization research. Existing metrics correlate weakly with human judgments and produce aggregate scores wit…

cs.CL2026

RoTRAG: Rule of Thumb Reasoning for Conversation Harm Detection with Retrieval-Augmented Generation

Juhyeon Lee, Wonduk Seo, Junseo Koh +3

Detecting harmful content in multi turn dialogue requires reasoning over the full conversational context rather than isolated utterances. However, most existing methods rely mainly…

cs.CL2025

ReviewGuard: Enhancing Deficient Peer Review Detection via LLM-Driven Data Augmentation

Haoxuan Zhang, Ruochi Li, Sarthak Shrestha +6

Peer review serves as the gatekeeper of science, yet the surge in submissions and widespread adoption of large language models (LLMs) in scholarly evaluation present unprecedented…

cs.CL2025

Unveiling the Merits and Defects of LLMs in Automatic Review Generation for Scientific Papers

Ruochi Li, Haoxuan Zhang, Edward Gehringer +3

The surge in scientific submissions has placed increasing strain on the traditional peer-review process, prompting the exploration of large language models (LLMs) for automated rev…

cs.CL20246 cited

A Comparative Study of Quality Evaluation Methods for Text Summarization

Huyen Nguyen, Haihua Chen, Lavanya Pobbathi +1

Evaluating text summarization has been a challenging task in natural language processing (NLP). Automatic metrics which heavily rely on reference summaries are not suitable in many…