Papers Implicatures
“Implicatures” 태그가 달린 논문 29편 · 필터 해제
Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges
Understanding pragmatics-the use of language in context-is crucial for developing NLP systems capable of interpreting nuanced language use. Despite recent advances in language technologies, including large language model…
ImplicaturesSurveyCan Vision-Language Models Infer Speaker's Ignorance? The Role of Visual and Linguistic Cues
This study investigates whether vision-language models (VLMs) can perform pragmatic inference, focusing on ignorance implicatures, utterances that imply the speaker's lack of precise knowledge. To test this, we systemati…
ImplicaturesInformativenessNeurosymbolic Graph Enrichment for Grounded World Models
The development of artificial intelligence systems capable of understanding and reasoning about complex real-world scenarios is a significant challenge. In this work we present a novel approach to enhance and exploit LLM…
Abstract Meaning RepresentationImplicaturesNatural Language UnderstandingDo language models capture implied discourse meanings? An investigation with exhaustivity implicatures of Korean morphology
Markedness in natural language is often associated with non-literal meanings in discourse. Differential Object Marking (DOM) in Korean is one instance of this phenomenon, where post-positional markers are selected based …
ImplicaturesObjectExperimental Pragmatics with Machines: Testing LLM Predictions for the Inferences of Plain and Embedded Disjunctions
Human communication is based on a variety of inferences that we draw from sentences, often going beyond what is literally said. While there is wide agreement on the basic distinction between entailment, implicature, and …
ImplicaturesDo Large Language Models Understand Conversational Implicature -- A case study with a chinese sitcom
Understanding the non-literal meaning of an utterance is critical for large language models (LLMs) to become human-like social communicators. In this work, we introduce SwordsmanImp, the first Chinese multi-turn-dialogue…
ImplicaturesMultiple-choiceProbing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics
Scalar adjectives pertain to various domain scales and vary in intensity within each scale (e.g. certain is more intense than likely on the likelihood scale). Scalar implicatures arise from the consideration of alternati…
DiversityImplicaturesRegularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning
We present a model of pragmatic language understanding, where utterances are produced and understood by searching for regularized equilibria of signaling games. In this model (which we call ReCo, for Regularized Conventi…
Implicatures"Is the Pope Catholic?" Applying Chain-of-Thought Reasoning to Understanding Conversational Implicatures
Conversational implicatures are pragmatic inferences that require listeners to deduce the intended meaning conveyed by a speaker from their explicit utterances. Although such inferential reasoning is fundamental to human…
ImplicaturesInteractive Acquisition of Fine-grained Visual Concepts by Exploiting Semantics of Generic Characterizations in Discourse
Interactive Task Learning (ITL) concerns learning about unforeseen domain concepts via natural interactions with human users. The learner faces a number of significant constraints: learning should be online, incremental …
AttributeImplicaturesPsycholinguistic Diagnosis of Language Models’ Commonsense Reasoning
Neural language models have attracted a lot of attention in the past few years. More and more researchers are getting intrigued by how language models encode commonsense, specifically what kind of commonsense they unders…
ImplicaturesTraining Compute-Optimal Large Language Models
We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget. We find that current large language models are significantly undertrained, a consequence …
AnachronismsAnalogical SimilarityAnalytic EntailmentCausal Judgment+69Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world. In this paper, we present an analysis o…
Abstract AlgebraAnachronismsAnalogical SimilarityAnalytic Entailment+143Pragmatic competence of pre-trained language models through the lens of discourse connectives
As pre-trained language models (LMs) continue to dominate NLP, it is increasingly important that we understand the depth of language capabilities in these models. In this paper, we target pre-trained LMs' competence in p…
ImplicaturesMachine Semiotics
Recognizing a basic difference between the semiotics of humans and machines presents a possibility to overcome the shortcomings of current speech assistive devices. For the machine, the meaning of a (human) utterance is …
Implicaturesspeech-recognitionSpeech RecognitionAre Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition
Natural language inference (NLI) is an increasingly important task for natural language understanding, which requires one to infer whether a sentence entails another. However, the ability of NLI models to make pragmatic …
DiagnosticImplicaturesNatural Language InferenceNatural Language Understanding+2Conversational implicatures in English dialogue: Annotated dataset
Human dialogue often contains utterances having meanings entirely different from the sentences used and are clearly understood by the interlocutors. But in human-computer interactions, the machine fails to understand the…
ImplicaturesCoverage of Information Extraction from Sentences and Paragraphs
Scalar implicatures are language features that imply the negation of stronger statements, e.g., {``}She was married twice{''} typically implicates that she was not married thrice. In this paper we discuss the importance …
ImplicaturesNegationControlled Natural Languages and Default Reasoning
Controlled natural languages (CNLs) are effective languages for knowledge representation and reasoning. They are designed based on certain natural languages with restricted lexicon and grammar. CNLs are unambiguous and s…
ImplicaturesLogical ReasoningQuestion AnsweringSensala: a Dynamic Semantics System for Natural Language Processing
Here we describe Sensala , an open source framework for the semantic interpretation of natural language that provides the logical meaning of a given text. The framework{'}s theory is based on a lambda calculus with excep…
Implicatures