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Academic research generates diverse data sources, and as researchers increasingly use machine learning to assist research tasks, a crucial question arises: Can we build a unified data interface to support the development of machine learning…

Computation and Language · Computer Science 2025-12-01 Jingjun Xu , Chongshan Lin , Haofei Yu , Tao Feng , Jiaxuan You

In theorem proving, the task of selecting useful premises from a large library to unlock the proof of a given conjecture is crucially important. This presents a challenge for all theorem provers, especially the ones based on language…

Artificial Intelligence · Computer Science 2022-05-24 Albert Q. Jiang , Wenda Li , Szymon Tworkowski , Konrad Czechowski , Tomasz Odrzygóźdź , Piotr Miłoś , Yuhuai Wu , Mateja Jamnik

Two-sample tests utilizing a similarity graph on observations are useful for high-dimensional and non-Euclidean data due to their flexibility and good performance under a wide range of alternatives. Existing works mainly focused on sparse…

Statistics Theory · Mathematics 2023-11-14 Yejiong Zhu , Hao Chen

Recent large-scale reasoning models have achieved state-of-the-art performance on challenging mathematical benchmarks, yet the internal mechanisms underlying their success remain poorly understood. In this work, we introduce the notion of a…

Artificial Intelligence · Computer Science 2025-10-02 Gouki Minegishi , Hiroki Furuta , Takeshi Kojima , Yusuke Iwasawa , Yutaka Matsuo

We introduce TechRank, a recursive algorithm based on a bi-partite graph with weighted nodes. We develop TechRank to link companies and technologies based on the method of reflection. We allow the algorithm to incorporate exogenous…

In recommender systems, user-item interactions can be modeled as a bipartite graph, where user and item nodes are connected by undirected edges. This graph-based view has motivated the rapid adoption of graph neural networks (GNNs), which…

Explainable Graph Neural Network (GNN) has emerged recently to foster the trust of using GNNs. Existing GNN explainers are developed from various perspectives to enhance the explanation performance. We take the first step to study GNN…

Cryptography and Security · Computer Science 2024-06-06 Jiate Li , Meng Pang , Yun Dong , Jinyuan Jia , Binghui Wang

Tool-integrated reasoning (TIR) has become a key approach for improving large reasoning models (LRMs) on complex problems. Prior work has mainly studied when to invoke tools, while overlooking how tools are applied. We identify two common…

Artificial Intelligence · Computer Science 2026-01-12 Ningning Xu , Yuxuan Jiang , Shubhashis Roy Dipta , Hengyuan Zhang

Many systems comprising entities in interactions can be represented as graphs, whose structure gives significant insights about how these systems work. Network theory has undergone further developments, in particular in relation to…

Data Analysis, Statistics and Probability · Physics 2016-06-14 Ronan Hamon , Pierre Borgnat , Patrick Flandrin , Céline Robardet

There is a long tradition of fruitful interaction between logic and social choice theory. In recent years, much of this interaction has focused on computer-aided methods such as SAT solving and interactive theorem proving. In this paper, we…

Logic in Computer Science · Computer Science 2021-10-19 Wesley H. Holliday , Chase Norman , Eric Pacuit

Aiming to offer a framework for blended learning to the teaching of proof theory, the present paper describes an interactive tutorial, called \textsc{TryLogic}, teaching how to solve logical conjectures either by proofs or refutations. The…

Computers and Society · Computer Science 2015-07-15 Patrick Terrematte , João Marcos

We propose a friend recommendation system (an application of link prediction) using edge embeddings on social networks. Most real-world social networks are multi-graphs, where different kinds of relationships (e.g. chat, friendship) are…

Social and Information Networks · Computer Science 2019-02-11 Janu Verma , Srishti Gupta , Debdoot Mukherjee , Tanmoy Chakraborty

Graph Neural Networks (GNNs) achieve state-of-the-art performance in various graph-related tasks. However, the black-box nature often limits their interpretability and trustworthiness. Numerous explainability methods have been proposed to…

Machine Learning · Computer Science 2023-11-13 Jialin Chen , Kenza Amara , Junchi Yu , Rex Ying

The evaluation of mathematical results plays a central role in assessing researchers' contributions and shaping the direction of the field. Currently, such evaluations rely primarily on human judgment, whether through journal peer review or…

Social and Information Networks · Computer Science 2026-03-31 Gergely Bérczi , Bin Dong , Haocheng Ju , Tianyi Xu

Graph transformers are a recent advancement in machine learning, offering a new class of neural network models for graph-structured data. The synergy between transformers and graph learning demonstrates strong performance and versatility…

Machine Learning · Computer Science 2025-12-23 Ahsan Shehzad , Feng Xia , Shagufta Abid , Ciyuan Peng , Shuo Yu , Dongyu Zhang , Karin Verspoor

Traditional proof systems involve a resource-bounded verifier communicating with a powerful (but untrusted) prover. Distributed verifier proof systems are a new family of proof models that involve a network of verifier nodes communicating…

Computational Complexity · Computer Science 2020-05-22 Nagaganesh Jaladanki , Wilson Wu

We propose a novel symbolic modeling framework for decision-making under risk that merges interpretability with the core insights of Prospect Theory. Our approach replaces opaque utility curves and probability weighting functions with…

Artificial Intelligence · Computer Science 2025-04-22 Ali Arslan Yousaf , Umair Rehman , Muhammad Umair Danish

We describe a prototype theorem prover, UTP2, developed to match the style of hand-written proof work in the Unifying Theories of Programming semantical framework. This is based on alphabetised predicates in a 2nd-order logic, with a strong…

Logic in Computer Science · Computer Science 2014-10-31 Andrew Butterfield

Interactive-proof games model the scenario where an honest party interacts with powerful but strategic provers, to elicit from them the correct answer to a computational question. Interactive proofs are increasingly used as a framework to…

Computer Science and Game Theory · Computer Science 2021-08-12 Jing Chen , Samuel McCauley , Shikha Singh

A logic for specification and verification is derived from the axioms of Zermelo-Fraenkel set theory. The proofs are performed using the proof assistant Isabelle. Isabelle is generic, supporting several different logics. Isabelle has the…

Logic in Computer Science · Computer Science 2008-02-03 Lawrence C. Paulson