20 papers · ranked by Valyu relevance
Yana Arkhipova, Alessandro Lopopolo, Shravan Vasishth, Milena Rabovsky
The N400 component of ERPs is modulated by how predictable a word is, but predictability is usually quantified with lexical cloze—the probability that readers supply that exact word in offline sentence completion tasks. This form-based metric is at odds with decades of evidence that the N400 is primarily sensitive to…
Anna Rysop, Lea-Maria Schmitt, Jonas Obleser, Gesa Hartwigsen
When speech intelligibility is reduced, listeners exploit constraints posed by semantic context to facilitate comprehension. The left angular gyrus (AG) has been argued to drive this semantic predictability gain. Taking a network perspective, we ask how the connectivity within language-specific and domain-general…
Pratik Bhandari, Vera Demberg, Jutta Kray
Previous studies have shown that at moderate levels of spectral degradation, semantic predictability facilitates language comprehension. It is argued that when speech is degraded, listeners have narrowed expectations about the sentence endings; i.e., semantic prediction may be limited to only most highly predictable…
Federica Magnabosco, Olaf Hauk
We used eye-tracking during natural reading to study how semantic control and representation mechanisms interact for the successful comprehension of sentences, by manipulating sentence context and single-word meaning. Specifically, we examined whether a word’s semantic characteristic (concreteness) affects first…
Mante S. Nieuwland, Dale J. Barr, Federica Bartolozzi, Simon Busch-Moreno + 19 more
What makes predictable words easier to process than unpredictable words (e.g., ‘bicycle’ compared to ‘elephant’ in “You never forget how to ride a bicycle/an elephant once you’ve learned”)? Are predictable words genuinely predicted, or simply more plausible and therefore easier to integrate with sentence context? We…
Jan Ketil Arnulf, Ulf Henning Olsson, Kim Nimon
This is a review of a range of empirical studies that use digital text algorithms to predict and model response patterns from humans to Likert-scale items, using texts only as inputs. The studies show that statistics used in construct validation is predictable on sample and individual levels, that this happens across…
Liling Xu, Sui Liu, Suiping Wang, Dongxia Sun + 1 more
The processing of words in sentence reading is influenced by both information from sentential context (the effect of predictability) and information from previewing upcoming words (the preview effect), but how both effects interact during online reading is not clear. In this study, we tested the interaction of…
Elisabeth F. Sterner, Andrea Greve, Franziska Knolle
Language impairments are core symptoms of both schizophrenia and autism spectrum disorders and have been linked to deficits in predictive language processing. While altered use of semantic predictions have been reported in both conditions, little is known whether semantic predictions are stable over time. The goal of…
Charles Jin, Martin Rinard
We present evidence that language models can learn meaning despite being trained only to perform next token prediction on text, specifically a corpus of programs. Each program is preceded by a specification in the form of (textual) input-output examples. Working with programs enables us to precisely define concepts…
Shaorong Yan, Gina R. Kuperberg, T. Florian Jaeger
The extent to which language processing involves prediction of upcoming inputs remains a question of ongoing debate. One important data point comes from 17 who reported that an N400-like event-related potential correlated with a probabilistic index of upcoming input. This result is often cited as evidence for gradient…
Bruno Bianchi, Gastón Bengolea Monzón, Luciana Ferrer, Diego Fernández Slezak + 2 more
'Diego Fernández Slezak' 'Diego E. Shalom' 'Juan E. Kamienkowski'] When we read printed text, we are continuously predicting upcoming words to integrate information and guide future eye movements. Thus, the Predictability of a given word has become one of the most important variables when explaining human behaviour and…
James A. Michaelov, Reeka Estacio, Zhang, Zhien + 1 more
Can language models reliably predict that possible events are more likely than merely improbable ones? By teasing apart possibility, typicality, and contextual relatedness, we show that despite the results of previous work, language models' ability to do this is far from robust. In fact, under certain conditions, all…
Anastasiya Lopukhina, Konstantin Lopukhin, Anna Laurinavichyute, Claudio Mulatti
'Claudio Mulatti'] During reading or listening, people can generate predictions about the lexical and morphosyntactic properties of upcoming input based on available context. Psycholinguistic experiments that study predictability or control for it conventionally rely on a human-based approach and estimate…
Chonghuan Zhang, Adarsh Arun, Alexei Lapkin
Computer Aided Synthesis Planning (CASP) development of reaction routes requires understanding of complete reaction structures. However, most reactions in the current databases are missing reaction co-participants. Although reaction prediction and atom mapping tools can predict major reaction participants and trace…
Mourad Mars, Mounir Zrigui, Mohamed Naceur Belgacem, Anis Zouaghi
This work is part of a large research project entitled "OrÈodule" aimed at developing tools for automatic speech recognition, translation, and synthesis for Arabic language. Our attention has mainly been focused on an attempt to improve the probabilistic model on which our semantic decoder is based. To achieve this…
Guy Emerson, Ann Copestake
Semantic composition remains an open problem for vector space models of semantics. In this paper, we explain how the probabilistic graphical model used in the framework of Functional Distributional Semantics can be interpreted as a probabilistic version of model theory. Building on this, we explain how various semantic…
Authors not listed
Early prediction of drug-induced organ toxicity remains a major bottleneck in drug discovery and clinical pharmacotherapy. Most data-driven toxicity models behave as endpoint predictors: they output a label but provide limited transparency about why a compound is risky or which evidence channel dominated the decision.…
Gemma Boleda
Distributional semantics provides multi-dimensional, graded, empirically induced word representations that successfully capture many aspects of meaning in natural languages, as shown in a large body of work in computational linguistics; yet, its impact in theoretical linguistics has so far been limited. This review…
Authors not listed
Large language models (LLMs) have shown promising potential across diverse chemistry tasks, including forward reaction prediction, retrosynthesis, and property prediction. However, their ability to capture the intrinsic chemistry of molecules remains unclear. To study this, we evaluate the consistency of…
Percy Liang
For building question answering systems and natural language interfaces, semantic parsing has emerged as an important and powerful paradigm. Semantic parsers map natural language into logical forms, the classic representation for many important linguistic phenomena. The modern twist is that we are interested in…