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20212026
most citedSubjective Bias in Abstractive Summarization

4 citations · 7 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.CL2025

Beyond Perplexity: Let the Reader Select Retrieval Summaries via Spectrum Projection Score

Zhanghao Hu, Qinglin Zhu, Siya Qi +3

Large Language Models (LLMs) have shown improved generation performance through retrieval-augmented generation (RAG) following the retriever-reader paradigm, which supplements mode…

cs.CL2025

NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning

Wei Liu, Siya Qi, Xinyu Wang +3

Recent advances such as DeepSeek R1-Zero highlight the effectiveness of incentive training, a reinforcement learning paradigm that computes rewards solely based on the final answer…

cs.CL2025

Evaluating LLMs' Assessment of Mixed-Context Hallucination Through the Lens of Summarization

Siya Qi, Rui Cao, Yulan He +1

With the rapid development of large language models (LLMs), LLM-as-a-judge has emerged as a widely adopted approach for text quality evaluation, including hallucination evaluation.…

cs.CL2025

EnigmaToM: Improve LLMs' Theory-of-Mind Reasoning Capabilities with Neural Knowledge Base of Entity States

Hainiu Xu, Siya Qi, Jiazheng Li +4

Theory-of-Mind (ToM), the ability to infer others' perceptions and mental states, is fundamental to human interaction but remains challenging for Large Language Models (LLMs). Whil…

cs.CL2025

Can LLMs Simulate L2-English Dialogue? An Information-Theoretic Analysis of L1-Dependent Biases

Rena Gao, Xuetong Wu, Tatsuki Kuribayashi +6

This study evaluates Large Language Models' (LLMs) ability to simulate non-native-like English use observed in human second language (L2) learners interfered with by their native f…