Zobrazeno 1 - 10
of 1 767
pro vyhledávání: '"Jong, C."'
Trolling in online communities typically involves disruptive behaviors such as provoking anger and manipulating discussions, leading to a polarized atmosphere and emotional distress. Robust moderation is essential for mitigating these negative impact
Externí odkaz:
http://arxiv.org/abs/2410.04164
Gloss-free Sign Language Translation (SLT) converts sign videos directly into spoken language sentences without relying on glosses. Recently, Large Language Models (LLMs) have shown remarkable translation performance in gloss-free methods by harnessi
Externí odkaz:
http://arxiv.org/abs/2408.10593
Publikováno v:
KnowledgeNLP@ACL 2024
Recent advancements in Large Language Models (LLMs) have significantly improved their performance across various Natural Language Processing (NLP) tasks. However, LLMs still struggle with generating non-factual responses due to limitations in their p
Externí odkaz:
http://arxiv.org/abs/2407.03627
Sign language, essential for the deaf and hard-of-hearing, presents unique challenges in translation and production due to its multimodal nature and the inherent ambiguity in mapping sign language motion to spoken language words. Previous methods oft
Externí odkaz:
http://arxiv.org/abs/2407.02854
Information retrieval models that aim to search for the documents relevant to the given query have shown many successes, which have been applied to diverse tasks. However, the query provided by the user is oftentimes very short, which challenges the
Externí odkaz:
http://arxiv.org/abs/2406.16013
Recent language models have shown remarkable performance on natural language understanding (NLU) tasks. However, they are often sub-optimal when faced with ambiguous samples that can be interpreted in multiple ways, over-confidently predicting a sing
Externí odkaz:
http://arxiv.org/abs/2406.09719
Social bias is shaped by the accumulation of social perceptions towards targets across various demographic identities. To fully understand such social bias in large language models (LLMs), it is essential to consider the composite of social perceptio
Externí odkaz:
http://arxiv.org/abs/2406.04064
The robustness of recent Large Language Models (LLMs) has become increasingly crucial as their applicability expands across various domains and real-world applications. Retrieval-Augmented Generation (RAG) is a promising solution for addressing the l
Externí odkaz:
http://arxiv.org/abs/2404.13948
Retrieval-Augmented Large Language Models (LLMs), which incorporate the non-parametric knowledge from external knowledge bases into LLMs, have emerged as a promising approach to enhancing response accuracy in several tasks, such as Question-Answering
Externí odkaz:
http://arxiv.org/abs/2403.14403
Large language models (LLMs) enable zero-shot approaches in open-domain question answering (ODQA), yet with limited advancements as the reader is compared to the retriever. This study aims at the feasibility of a zero-shot reader that addresses the c
Externí odkaz:
http://arxiv.org/abs/2310.17490