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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

collaborators

12 papers

physics.flu-dyn2026

SAGE-PINN: A Singularity-free Axisymmetric Geometry-Encoded Physics-Informed Neural Network for Axisymmetric Multiphysics Flow in Cylindrical Coordinates

Raj Maurya, Joyprakash Akhuli, Doyel Pandey

Physics-informed neural networks (PINNs) provide a mesh-free framework for multiphysics modeling, yet fluid flow in axisymmetric cylindrical coordinates remains largely unexplored…

cs.CL2026

Lexical Perturbations Disrupt LLM Reasoning: An Empirical Study of Attention Diversion

Jiaqian Zhu, Yang Zhang, Junhua Ding +1

Large Language Models (LLMs) achieve strong reasoning performance, but their robustness to realistic lexical corruption remains poorly understood. We evaluate four open-weight inst…

cs.CL2026

OCR-Memory: Optical Context Retrieval for Long-Horizon Agent Memory

Jinze Li, Yang Zhang, Xin Yang +5

Autonomous LLM agents increasingly operate in long-horizon, interactive settings where success depends on reusing experience accumulated over extended histories. However, existing…

cs.AI2026

MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation

Haoxuan Zhang, Ruochi Li, Yang Zhang +4

The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Model and Data Cards is not scal…

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.AI2026

AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation

Haoxuan Zhang, Ruochi Li, Zhenni Liang +7

Transparent and standardized documentation is essential for building trustworthy generative AI (GAI) systems. However, existing automated methods for generating model and data card…

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.DL2025

Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator

Haoxuan Zhang, Ruochi Li, Yang Zhang +4

Large language models (LLMs) are increasingly used in scientific research and discovery, supporting tasks ranging from literature retrieval and synthesis to hypothesis generation,…

cs.CL2024★ 6 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…

cs.LG2024★ 5 cited

A Survey on Data Quality Dimensions and Tools for Machine Learning

Yuhan Zhou, Fengjiao Tu, Kewei Sha +2

Machine learning (ML) technologies have become substantial in practically all aspects of our society, and data quality (DQ) is critical for the performance, fairness, robustness, s…