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cs.CL2026
G^2C-MT: Graph-Guided Context Selection for Document-Level Machine Translation
Baijun Ji, Zixuan Zhou, Xiangyu Duan +4
Effective document-level machine translation (DocMT) requires capturing long-range discourse dependencies. Recent work has explored retrieval-based and discourse-aware context sele…
cs.CL2026
PolySpeech-100: A Large-Scale Benchmark for Speech Understanding Across 100+ Languages and Dialects
Sicheng Yang, Shulan Ruan, Shiwei Wu +4
While End-to-End (E2E) Speech-Large Language Models (Speech-LLMs) are rapidly evolving, their evaluation methodologies remain limited to the era of simple transcription. Existing b…
cs.CL2024★ 1 cited
The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Pre-trained Language Models
Yan Liu, Yu Liu, Xiaokang Chen +4
Pre-trained Language models (PLMs) have been acknowledged to contain harmful information, such as social biases, which may cause negative social impacts or even bring catastrophic…