7 papers
FactNet: A Billion-Scale Knowledge Graph for Multilingual Factual Grounding
Yingli Shen, Wen Lai, Jie Zhou +7
Large language models hallucinate factual claims and struggle to ground their outputs in retrievable evidence, particularly in non-English languages. Existing resources impose a tr…
DiffScore: Text Evaluation Beyond Autoregressive Likelihood
Wen Lai, Yingli Shen, Dingnan Jin +4
Autoregressive language models are widely used for text evaluation, however, their left-to-right factorization introduces positional bias, i.e., early tokens are scored with only l…
MEIC-DT: Memory-Efficient Incremental Clustering for Long-Text Coreference Resolution with Dual-Threshold Constraints
Kangyang Luo, Shuzheng Si, Yuzhuo Bai +8
In the era of large language models (LLMs), supervised neural methods remain the state-of-the-art (SOTA) for Coreference Resolution. Yet, their full potential is underexplored, par…
ImCoref-CeS: An Improved Lightweight Pipeline for Coreference Resolution with LLM-based Checker-Splitter Refinement
Kangyang Luo, Yuzhuo Bai, Shuzheng Si +9
Coreference Resolution (CR) is a critical task in Natural Language Processing (NLP). Current research faces a key dilemma: whether to further explore the potential of supervised ne…
DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly Detection
Yingli Shen, Wen Lai, Shuo Wang +4
The rapid development of multilingual large language models (LLMs) highlights the need for high-quality, diverse, and well-curated multilingual datasets. In this paper, we introduc…
From Unaligned to Aligned: Scaling Multilingual LLMs with Multi-Way Parallel Corpora
Yingli Shen, Wen Lai, Shuo Wang +4
Continued pretraining and instruction tuning on large-scale multilingual data have proven to be effective in scaling large language models (LLMs) to low-resource languages. However…