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cs.CL2025
Enhancing Faithfulness in Abstractive Summarization via Span-Level Fine-Tuning
Sicong Huang, Qianqi Yan, Shengze Wang +1
Abstractive summarization using large language models (LLMs) has become an essential tool for condensing information. However, despite their ability to generate fluent summaries, t…
cs.CL2025
ReliableMath: Benchmark of Reliable Mathematical Reasoning on Large Language Models
Boyang Xue, Qi Zhu, Rui Wang +8
Although demonstrating remarkable performance on reasoning tasks, Large Language Models (LLMs) still tend to fabricate unreliable responses when confronted with problems that are u…