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200 papers

While Large Language Models (LLMs) are widely used in open-domain Question Answering (QA), their ability to handle inferential questions-where answers must be derived rather than directly retrieved-remains still underexplored. This study…

Computation and Language · Computer Science 2026-05-13 Jamshid Mozafari , Bhawna Piryani , Adam Jatowt

Game semantics and winning strategies offer a potential conceptual bridge between semantics and proof systems of logics. We illustrate this link for hybrid logic -- an extension of modal logic that allows for explicit reference to worlds…

Logic in Computer Science · Computer Science 2022-06-02 Robert Freiman

Autoregressive Large Language Models (LLMs) trained for next-word prediction have demonstrated remarkable proficiency at producing coherent text. But are they equally adept at forming coherent probability judgments? We use probabilistic…

Computation and Language · Computer Science 2025-05-07 Jian-Qiao Zhu , Thomas L. Griffiths

This paper is an informal survey of some of the deep connections between logic and optimization. It covers George Boole's probability logic, decision diagrams, logic and cutting planes, first order predicate logic, default and nonmonotonic…

Logic · Mathematics 2019-10-31 John Hooker

Logic has its origins in basic questions about the nature of the real world and how we describe it. This article seeks to bring out the physical and epistemological relevance of some of the more recent technical work in logic and…

Logic · Mathematics 2011-09-08 S. Barry Cooper

With the increasing interest in using large language models (LLMs) for planning in natural language, understanding their behaviors becomes an important research question. This work conducts a systematic investigation of LLMs' ability to…

Computation and Language · Computer Science 2025-02-18 Yixuan Wang , Freda Shi

Incorporating large language models (LLMs) in medical question answering demands more than high average accuracy: a model that returns substantively different answers each time it is queried is not a reliable medical tool. Online health…

Information Retrieval · Computer Science 2026-04-14 Avi-ad Avraam Buskila

The LLMJudge challenge is organized as part of the LLM4Eval workshop at SIGIR 2024. Test collections are essential for evaluating information retrieval (IR) systems. The evaluation and tuning of a search system is largely based on relevance…

This volume contains the proceedings of the 12th International Workshop on Quantum Physics and Logic (QPL 2015), which was held July 15-17, 2015 at Oxford University. The goal of this workshop series is to bring together researchers working…

Quantum Physics · Physics 2015-11-05 Chris Heunen , Peter Selinger , Jamie Vicary

The emergence of discourse-like tokens such as "wait" and "therefore" in large language models (LLMs) has offered a unique window into their reasoning processes. However, systematic analyses of how such signals vary across training…

Computation and Language · Computer Science 2026-01-27 Jaehui Hwang , Dongyoon Han , Sangdoo Yun , Byeongho Heo

Large language models (LLMs) excel at complex tasks with advances in reasoning capabilities. However, existing reward mechanisms remain tightly coupled to final correctness and pay little attention to the underlying reasoning process:…

Machine Learning · Computer Science 2026-05-14 Jingyao Wang , Peizheng Guo , Wenwen Qiang , Jiahuan Zhou , Huijie Guo , Changwen Zheng , Hui Xiong

Biomedical text mining and question-answering are essential yet highly demanding tasks, particularly in the face of the exponential growth of biomedical literature. In this work, we present our participation in the 13th edition of the…

Computation and Language · Computer Science 2025-08-05 Dimitra Panou , Alexandros C. Dimopoulos , Manolis Koubarakis , Martin Reczko

Our paper presents team MasonTigers submission to the SemEval-2024 Task 9 - which provides a dataset of puzzles for testing natural language understanding. We employ large language models (LLMs) to solve this task through several prompting…

Computation and Language · Computer Science 2024-04-04 Md Nishat Raihan , Dhiman Goswami , Al Nahian Bin Emran , Sadiya Sayara Chowdhury Puspo , Amrita Ganguly , Marcos Zampieri

Questions combine our mastery of language with our remarkable facility for reasoning about uncertainty. How do people navigate vast hypothesis spaces to pose informative questions given limited cognitive resources? We study these tradeoffs…

Computation and Language · Computer Science 2024-05-03 Gabriel Grand , Valerio Pepe , Jacob Andreas , Joshua B. Tenenbaum

Large language models (LLMs) exhibit the ability to generalize given few-shot examples in their input prompt, an emergent capability known as in-context learning (ICL). We investigate whether LLMs use ICL to perform structured reasoning in…

Computation and Language · Computer Science 2025-07-01 Ritwik Gupta , Rodolfo Corona , Jiaxin Ge , Eric Wang , Dan Klein , Trevor Darrell , David M. Chan

This volume constitutes the proceedings of LFMTP 2015, the Tenth International Workshop on Logical Frameworks and Meta-Languages: Theory and Practice, held on August 1st, 2015 in Berlin, Germany. The workshop was a one-day satellite event…

Logic in Computer Science · Computer Science 2015-07-29 Iliano Cervesato , Kaustuv Chaudhuri

This article surveys recent advances in applying algebraic techniques to constraint satisfaction problems.

Logic in Computer Science · Computer Science 2007-05-23 Hubie Chen

We show how solutions to many recursive arena equations can be computed in a natural way by allowing loops in arenas. We then equip arenas with winning functions and total winning strategies. We present two natural winning conditions…

Logic in Computer Science · Computer Science 2010-01-06 Pierre Clairambault

In the field of information retrieval, Query Likelihood Models (QLMs) rank documents based on the probability of generating the query given the content of a document. Recently, advanced large language models (LLMs) have emerged as effective…

Information Retrieval · Computer Science 2023-10-23 Shengyao Zhuang , Bing Liu , Bevan Koopman , Guido Zuccon

Combinatorial games lead to several interesting, clean problems in algorithms and complexity theory, many of which remain open. The purpose of this paper is to provide an overview of the area to encourage further research. In particular, we…

Computational Complexity · Computer Science 2009-09-25 Erik D. Demaine , Robert A. Hearn