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Reto Gubelmann
Title
Dr.
Last Name
Gubelmann
First name
Reto
Email
reto.gubelmann@unisg.ch
Phone
+41 71 224 75 25
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1 - 10 of 13
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PublicationLarge Language Models, Agency, and Why Speech Acts are Beyond Them (For Now) - A Kantian-Cum-Pragmatist CaseThis article sets in with the question whether current or foreseeable transformer-based large language models (LLMs), such as the ones powering OpenAI's ChatGPT, could be language users in a way comparable to humans. It answers the question negatively, presenting the following argument. Apart from niche uses, to use language means to act. But LLMs are unable to act because they lack intentions. This, in turn, is because they are the wrong kind of being: agents with intentions need to be autonomous organisms while LLMs are heteronomous mechanisms. To conclude, the article argues, based on structural aspects of transformer-based LLMs, that these LLMs have taken a first step away from mechanistic artificiality to autonomous self-constitution, which means that these models are (slowly) moving into a direction that someday might result in non-human, but equally non-artificial agents, thus subverting the time-honored Kantian distinction between organism and mechanism.Type: journal articleJournal: Philosophy & Technology
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PublicationCapturing the Varieties of Natural Language Inference: A Systematic Survey of Existing Datasets and Two Novel Benchmarks( 2023-11-20)
;Katis, IoannisTransformer-based Pre-Trained Language Models currently dominate the field of Natural Language Inference (NLI). We first survey existing NLI datasets, and we systematize them according to the different kinds of logical inferences that are being distinguished. This shows two gaps in the current dataset landscape, which we propose to address with one dataset that has been developed in argumentative writing research as well as a new one building on syllogistic logic. Throughout, we also explore the promises of ChatGPT. Our results show that our new datasets do pose a challenge to existing methods and models, including ChatGPT, and that tackling this challenge via fine-tuning yields only partly satisfactory results.Type: journal articleJournal: Journal of Logic, Language and Information -
PublicationContext Matters: A Pragmatic Study of PLMs’ Negation UnderstandingIn linguistics, there are two main perspectives on negation: a semantic and a pragmatic view. So far, research in NLP on negation has almost exclusively adhered to the semantic view. In this article, we adopt the pragmatic paradigm to conduct a study of negation understanding focusing on transformer-based PLMs. Our results differ from previous, semantics-based studies and therefore help to contribute a more comprehensive – and, given the results, much more optimistic – picture of the PLMs’ negation understanding.Type: journal articleJournal: Proceedings of the 60th Annual Meeting of the Association for Computational LinguisticsVolume: 1
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PublicationType: journal articleVolume: 04/2022
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PublicationType: journal article
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PublicationA Philosophically-Informed Contribution to the Generalization Problem of Neural Natural Language Inference: Shallow Heuristics, Bias, and the Varieties of Inference(Association for Computational Linguistics, 2022)Type: journal article
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PublicationMaddy vs. Quine on Innate Concepts. Revisiting A Perennial Debate in Light of Recent Empirical ResultsIn his posthumously published work, Quine abandons his empiricist principle that humans do not have any innate concepts, or knowledge. He does so in light of empirical research that Penelope Maddy capitalizes on to develop her own naturalized epistemology. The empirical research in question is due to the pioneering work of developmental psychologist Elisabeth Spelke. Spelke employs the method of habituation and preferential looking to argue that human infants have innate concepts, and that they have some knowledge about what can and cannot happen to physical objects. Taking into account empirical studies as well as methodological considerations, this article examines whether this research can support these strong philosophical conclusions drawn from it, finding that it likely cannot provide such support.Type: journal articleJournal: PhilosophiaVolume: 48
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PublicationFROM SHARED STIMULI TO PREESTABLISHED HARMONY: THE DEVELOPMENT OF QUINE’S THINKING ON INTERSUBJECTIVITY AND OBJECTIVE VALIDITY( 2019-10)W. V. O. Quine is generally seen as one of the foremost empiricists of the twentieth century. For large parts of his career, the label “empiricist” is accurate; in his mature work, however, he integrated decidedly antiempiricist elements in his epistemology. From The Roots of Reference onward, he enlists natural selection and innate cognitive structures to ensure that scientific concepts have a “degree of objective validity.” From From Stimulus to Science onward, he also explains the very possibility of communication via a preestablished harmony of innate cognitive structures that is guaranteed by natural selection. This article reconstrues the reasons that compelled Quine to these commitments, and it details the development of Quine’s thinking on these topics across more than 3 decades; in particular, the article argues that recognizing that so-called stimulus meanings are private decisively shaped Quine’s views. By means of a critical evaluation, the article argues that natural selection can make plausible that scientific concepts have a degree of objective validity—if this Quinean claim is properly understood; in contrast, the article suggests, with recourse to research by Robert C. Richardson, that it is doubtful whether natural selection can underpin the preestablished harmony that Quine requires to explain communication.Type: journal articleJournal: HOPOS: The Journal of the International Society for the History of Philosophy of ScienceVolume: 9
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PublicationExploring the Usefulness of Open and Proprietary LLMs in Argumentative Writing Support( 2024-07-02)In this article, we present the results of an exploratory study conducted with our self-developed tool Artist. The goal of the tool is to give formative feedback to develop students' argumentation skills. We compare the feedback that two different LLMs, an open-sourced one by META and one of OpenAI's fully proprietary ones, give to students' argumentative writing. We find that, overall, students find the feedback provided by both LLMs helpful (7.51 vs. 7.65 on a scale from 1 to 10), and they rate the quality of the feedback as good to very good. We take this as a very encouraging provisional result that invites larger and more extensive studies on the topic.Type: conference paper
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PublicationWhen Truth Matters - Addressing Pragmatic Categories in Natural Language Inference (NLI) by Large Language Models (LLMs)( 2023-07)
;Kalouli, Aikaterini-LidaIn this paper, we focus on the ability of large language models (LLMs) to accommodate different pragmatic sentence types, such as questions, commands, as well as sentence fragments for natural language inference (NLI). On the commonly used notion of logical inference, nothing can be inferred from a question, a command, or an incomprehensible sentence fragment. We find MNLI, arguably the most important NLI dataset, and hence models fine-tuned on this dataset, insensitive to this fact. Using a symbolic semantic parser, we develop and make publicly available, fine-tuning datasets designed specifically to address this issue, with promising results. We also make a first exploration of ChatGPT's concept of entailment.Type: conference paperJournal: Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)