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Sarcasm is a pragmatic phenomenon in which speakers convey meanings that diverge from literal content, relying on an interaction between semantics and prosodic expression. However, how these cues jointly contribute to the recognition of…

计算与语言 · 计算机科学 2026-02-04 Zhu Li , Yuqing Zhang , Xiyuan Gao , Shekhar Nayak , Matt Coler

Language Models (LMs) have demonstrated impressive capabilities in solving complex reasoning tasks, particularly when prompted to generate intermediate explanations. However, it remains an open question whether these intermediate reasoning…

计算与语言 · 计算机科学 2025-02-25 Moritz Miller , Kumar Shridhar

The reasoning abilities of Large Language Models (LLMs) are becoming a central focus of study in NLP. In this paper, we consider the case of syllogistic reasoning, an area of deductive reasoning studied extensively in logic and cognitive…

计算与语言 · 计算机科学 2024-10-18 Leonardo Bertolazzi , Albert Gatt , Raffaella Bernardi

Predicting context-dependent and non-literal utterances like sarcastic and ironic expressions still remains a challenging task in NLP, as it goes beyond linguistic patterns, encompassing common sense and shared knowledge as crucial…

计算与语言 · 计算机科学 2018-09-27 Suzana Ilić , Edison Marrese-Taylor , Jorge A. Balazs , Yutaka Matsuo

Recent LLMs like DeepSeek-R1 have demonstrated state-of-the-art performance by integrating deep thinking and complex reasoning during generation. However, the internal mechanisms behind these reasoning processes remain unexplored. We…

Intent, typically clearly formulated and planned, functions as a cognitive framework for communication and problem-solving. This paper introduces the concept of Speaking with Intent (SWI) in large language models (LLMs), where the…

计算与语言 · 计算机科学 2025-09-12 Yuwei Yin , EunJeong Hwang , Giuseppe Carenini

Large Language Models (LLMs) have shown remarkable performance in various natural language processing tasks but face challenges in mathematical reasoning, where complex problem-solving requires both linguistic understanding and mathematical…

计算与语言 · 计算机科学 2025-03-20 Shuguang Chen , Guang Lin

A recent study (Kuribayashi et al., 2025) has shown that human sentence processing behavior, typically measured on syntactically unchallenging constructions, can be effectively modeled using surprisal from early layers of large language…

计算与语言 · 计算机科学 2026-04-21 Tatsuki Kuribayashi , Alex Warstadt , Yohei Oseki , Ethan Gotlieb Wilcox

Sarcasm is a form of speech in which speakers say the opposite of what they truly mean in order to convey a strong sentiment. In other words, "Sarcasm is the giant chasm between what I say, and the person who doesn't get it.". In this paper…

计算与语言 · 计算机科学 2017-04-25 Lotem Peled , Roi Reichart

Large language models (LLMs) increasingly exhibit human-like patterns of pragmatic and social reasoning. This paper addresses two related questions: do LLMs approximate human social meaning not only qualitatively but also quantitatively,…

计算与语言 · 计算机科学 2026-04-06 Roland Mühlenbernd

Research in AI using Large-Language Models (LLMs) is rapidly evolving, and the comparison of their performance with human reasoning has become a key concern. Prior studies have indicated that LLMs and humans share similar biases, such as…

计算与语言 · 计算机科学 2026-03-09 Hirohiko Abe , Risako Ando , Takanobu Morishita Kentaro Ozeki , Koji Mineshima , Mitsuhiro Okada

Over the past few years, the abilities of large language models (LLMs) have received extensive attention, which have performed exceptionally well in complicated scenarios such as logical reasoning and symbolic inference. A significant…

计算与语言 · 计算机科学 2024-02-20 Junbing Yan , Chengyu Wang , Jun Huang , Wei Zhang

Inductive reasoning is a core problem-solving capacity: humans can identify underlying principles from a few examples, which robustly generalize to novel scenarios. Recent work evaluates large language models (LLMs) on inductive reasoning…

机器学习 · 计算机科学 2024-06-03 Ruocheng Wang , Eric Zelikman , Gabriel Poesia , Yewen Pu , Nick Haber , Noah D. Goodman

Large language models (LLMs) have demonstrated impressive capabilities in various reasoning tasks, aided by techniques like chain-of-thought prompting that elicits verbalized reasoning. However, LLMs often generate text with obvious…

人工智能 · 计算机科学 2024-12-06 Zhihui Xie , Jizhou Guo , Tong Yu , Shuai Li

We introduce a deep neural network for automated sarcasm detection. Recent work has emphasized the need for models to capitalize on contextual features, beyond lexical and syntactic cues present in utterances. For example, different…

计算与语言 · 计算机科学 2016-07-06 Silvio Amir , Byron C. Wallace , Hao Lyu , Paula Carvalho Mário J. Silva

Subjective language understanding refers to a broad set of natural language processing tasks where the goal is to interpret or generate content that conveys personal feelings, opinions, or figurative meanings rather than objective facts.…

计算与语言 · 计算机科学 2025-08-12 Changhao Song , Yazhou Zhang , Hui Gao , Ben Yao , Peng Zhang

Understanding human intents from multimodal signals is critical for analyzing human behaviors and enhancing human-machine interactions in real-world scenarios. However, existing methods exhibit limitations in their modality-level reliance,…

多媒体 · 计算机科学 2025-09-03 Qianrui Zhou , Hua Xu , Yifan Wang , Xinzhi Dong , Hanlei Zhang

Sarcasm typically conveys emotions of contempt or criticism by expressing a meaning that is contrary to the speaker's true intent. Accurate detection of sarcasm aids in identifying and filtering undesirable information on the Internet,…

计算与语言 · 计算机科学 2024-12-18 Tongguan Wang , Junkai Li , Guixin Su , Yongcheng Zhang , Dongyu Su , Yuxue Hu , Ying Sha

The prevalence of sarcasm in multimodal dialogues on the social platforms presents a crucial yet challenging task for understanding the true intent behind online content. Comprehensive sarcasm analysis requires two key aspects: Multimodal…

计算与语言 · 计算机科学 2026-03-31 Diandian Guo , Fangfang Yuan , Cong Cao , Xixun Lin , Chuan Zhou , Hao Peng , Yanan Cao , Yanbing Liu

Current Large Language Models (LLMs) are unparalleled in their ability to generate grammatically correct, fluent text. LLMs are appearing rapidly, and debates on LLM capacities have taken off, but reflection is lagging behind. Thus, in this…

计算与语言 · 计算机科学 2023-11-01 Bram M. A. van Dijk , Tom Kouwenhoven , Marco R. Spruit , Max J. van Duijn