activity
20242026
most citedWatermark-based Attribution of AI-Generated Content

6 citations · 8 across the 24 of their papers we have counts for

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9 papers · 1 filter

cs.CL2026

RankLLM: Weighted Ranking of LLMs by Quantifying Question Difficulty

Ziqian Zhang, Xingjian Hu, Yue Huang +8

Benchmarks establish a standardized evaluation framework to systematically assess the performance of large language models (LLMs), facilitating objective comparisons and driving ad…

cs.CL2026

Copyright Detective: A Forensic System to Evidence LLMs Flickering Copyright Leakage Risks

Guangwei Zhang, Jianing Zhu, Cheng Qian +12

We present Copyright Detective, the first interactive forensic system for detecting, analyzing, and visualizing potential copyright risks in LLM outputs. The system treats copyrigh…

cs.CL2025

A Survey on Post-training of Large Language Models

Guiyao Tie, Zeli Zhao, Dingjie Song +23

The emergence of Large Language Models (LLMs) has fundamentally transformed natural language processing, making them indispensable across domains ranging from conversational system…

cs.CL2025

ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods

Roy Xie, Junlin Wang, Ruomin Huang +5

The rapid scaling of large language models (LLMs) has raised concerns about the transparency and fair use of the data used in their pretraining. Detecting such content is challengi…

cs.CL2025

StringLLM: Understanding the String Processing Capability of Large Language Models

Xilong Wang, Hao Fu, Jindong Wang +1

String processing, which mainly involves the analysis and manipulation of strings, is a fundamental component of modern computing. Despite the significant advancements of large lan…

cs.CL2024

TrustLLM: Trustworthiness in Large Language Models

Yue Huang, Lichao Sun, Haoran Wang +67

Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural language processing capabilities. Nonetheless, these LLMs prese…