4 citations · 20 across the 28 of their papers we have counts for
6 papers · 1 filter
Loss-Aware Curriculum Learning for Chinese Grammatical Error Correction
Ding Zhang, Yangning Li, Lichen Bai +6
Chinese grammatical error correction (CGEC) aims to detect and correct errors in the input Chinese sentences. Recently, Pre-trained Language Models (PLMS) have been employed to imp…
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent
Yangning Li, Yinghui Li, Xinyu Wang +8
Multimodal Retrieval Augmented Generation (mRAG) plays an important role in mitigating the "hallucination" issue inherent in multimodal large language models (MLLMs). Although prom…
UltraWiki: Ultra-fine-grained Entity Set Expansion with Negative Seed Entities
Yangning Li, Qingsong Lv, Tianyu Yu +5
Entity Set Expansion (ESE) aims to identify new entities belonging to the same semantic class as the given set of seed entities. Traditional methods solely relied on positive seed…
Evaluating Robustness of Generative Search Engine on Adversarial Factual Questions
Xuming Hu, Xiaochuan Li, Junzhe Chen +8
Generative search engines have the potential to transform how people seek information online, but generated responses from existing large language models (LLMs)-backed generative s…
Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction
Yinghui Li, Shang Qin, Haojing Huang +6
Recently, Large Language Models (LLMs) have been widely studied by researchers for their roles in various downstream NLP tasks. As a fundamental task in the NLP field, Chinese Gram…
When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models
Yinghui Li, Qingyu Zhou, Yuanzhen Luo +5
Recently, Large Language Models (LLMs) make remarkable evolutions in language understanding and generation. Following this, various benchmarks for measuring all kinds of capabiliti…