Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Wei, Lingwei"'
Multimodal fact verification is an under-explored and emerging field that has gained increasing attention in recent years. The goal is to assess the veracity of claims that involve multiple modalities by analyzing the retrieved evidence. The main cha
Externí odkaz:
http://arxiv.org/abs/2407.10474
Many fake news detection studies have achieved promising performance by extracting effective semantic and structure features from both content and propagation trees. However, it is challenging to apply them to practical situations, especially when us
Externí odkaz:
http://arxiv.org/abs/2407.09894
This paper proposes an information-theoretic representation learning framework, named conditional information flow maximization, to extract noise-invariant sufficient representations for the input data and target task. It promotes the learned represe
Externí odkaz:
http://arxiv.org/abs/2406.05510
This paper presents a new supervised representation learning framework, namely structured probabilistic coding (SPC), to learn compact and informative representations from input related to the target task. SPC is an encoder-only probabilistic coding
Externí odkaz:
http://arxiv.org/abs/2312.13933
Large Language Models (LLMs) have garnered significant attention for their powerful ability in natural language understanding and reasoning. In this paper, we present a comprehensive empirical study to explore the performance of LLMs on misinformatio
Externí odkaz:
http://arxiv.org/abs/2311.12699
Extracting generalized and robust representations is a major challenge in emotion recognition in conversations (ERC). To address this, we propose a supervised adversarial contrastive learning (SACL) framework for learning class-spread structured repr
Externí odkaz:
http://arxiv.org/abs/2306.01505
This paper describes our system designed for SemEval-2023 Task 12: Sentiment analysis for African languages. The challenge faced by this task is the scarcity of labeled data and linguistic resources in low-resource settings. To alleviate these, we pr
Externí odkaz:
http://arxiv.org/abs/2306.01093
The emotion recognition in conversation (ERC) task aims to predict the emotion label of an utterance in a conversation. Since the dependencies between speakers are complex and dynamic, which consist of intra- and inter-speaker dependencies, the model
Externí odkaz:
http://arxiv.org/abs/2206.03173
The Emotion-Cause Pair Extraction (ECPE) task aims to extract emotions and causes as pairs from documents. We observe that the relative distance distribution of emotions and causes is extremely imbalanced in the typical ECPE dataset. Existing methods
Externí odkaz:
http://arxiv.org/abs/2205.02132
Emotion Recognition in Conversations (ERC) has considerable prospects for developing empathetic machines. For multimodal ERC, it is vital to understand context and fuse modality information in conversations. Recent graph-based fusion methods generall
Externí odkaz:
http://arxiv.org/abs/2203.02385