반응형 오늘의 자연어 처리572 [2022-11-27] 오늘의 자연어처리 Sarcasm Detection Framework Using Emotion and Sentiment Features Sarcasm detection is an essential task that can help identify the actual sentiment in user-generated data, such as discussion forums or tweets. Sarcasm is a sophisticated form of linguistic expression because its surface meaning usually contradicts its inner, deeper meaning. Such incongruity is the essential component of sarcasm, h.. 2022. 11. 27. [2022-11-26] 오늘의 자연어처리 Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning To overcome the data sparsity issue in short text topic modeling, existing methods commonly rely on data augmentation or the data characteristic of short texts to introduce more word co-occurrence information. However, most of them do not make full use of the augmented data or the data characteristic: t.. 2022. 11. 26. [2022-11-25] 오늘의 자연어처리 Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks Recently, there has been significant progress in teaching language models to perform step-by-step reasoning to solve complex numerical reasoning tasks. Chain-of-thoughts prompting (CoT) is by far the state-of-art method for these tasks. CoT uses language models to perform both reasoning and comp.. 2022. 11. 25. [2022-11-24] 오늘의 자연어처리 HaRiM$^+$: Evaluating Summary Quality with Hallucination Risk One of the challenges of developing a summarization model arises from the difficulty in measuring the factual inconsistency of the generated text. In this study, we reinterpret the decoder overconfidence-regularizing objective suggested in (Miao et al., 2021) as a hallucination risk measurement to better estimate the quality of genera.. 2022. 11. 24. 이전 1 ··· 105 106 107 108 109 110 111 ··· 143 다음 반응형