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This paper demonstrates that artificial intelligence can accelerate mathematical discovery by autonomously solving an open problem in theoretical physics. We present a neuro-symbolic system, combining the Gemini Deep Think large language…

Artificial Intelligence · Computer Science 2026-03-06 Michael P. Brenner , Vincent Cohen-Addad , David Woodruff

Recent advances in large language models (LLMs) have opened new avenues for accelerating scientific research. While models are increasingly capable of assisting with routine tasks, their ability to contribute to novel, expert-level…

Recent advances in foundational models have yielded reasoning systems capable of achieving a gold-medal standard at the International Mathematical Olympiad. The transition from competition-level problem-solving to professional research,…

Large language models (LLMs) increasingly excel at mathematical reasoning, but their unreliability limits their utility in mathematics research. A mitigation is using LLMs to generate formal proofs in languages like Lean. We perform the…

As automated reasoning systems advance rapidly, there is a growing need for research-level formal mathematical problems to accurately evaluate their capabilities. To address this, we present Formal Conjectures, an evolving benchmark of…

Math reasoning is becoming an ever increasing area of focus as we scale large language models. However, even the previously-toughest evals like MATH are now close to saturated by frontier models (90.0% for o1-mini and 86.5% for Gemini 1.5…

Machine Learning · Computer Science 2024-12-13 Albert S. Yue , Lovish Madaan , Ted Moskovitz , DJ Strouse , Aaditya K. Singh

Artificial intelligence (AI) has demonstrated impressive progress in mathematical reasoning, yet its integration into the practice of mathematical research remains limited. In this study, we investigate how the AI Mathematician (AIM) system…

Artificial Intelligence · Computer Science 2025-10-31 Yuanhang Liu , Beichen Wang , Peng Li , Yang Liu

Can artificial intelligence truly contribute to creative mathematical research, or does it merely automate routine calculations while introducing risks of error? We provide empirical evidence through a detailed case study: the discovery of…

Artificial Intelligence · Computer Science 2026-04-17 Tan Bui-Thanh

The mathematical capabilities of AI systems are complex and multifaceted. Most existing research has predominantly focused on the correctness of AI-generated solutions to mathematical problems. In this work, we argue that beyond producing…

Computation and Language · Computer Science 2024-10-25 Junyi Ye , Jingyi Gu , Xinyun Zhao , Wenpeng Yin , Guiling Wang

The rapid advancement of Large Language Models (LLMs) presents a significant challenge to academic integrity within computing education. As educators seek reliable detection methods, this paper evaluates the capacity of three prominent LLMs…

Computers and Society · Computer Science 2025-12-30 Christopher Burger , Karmece Talley , Christina Trotter

This work introduces Gemma, a family of lightweight, state-of-the art open models built from the research and technology used to create Gemini models. Gemma models demonstrate strong performance across academic benchmarks for language…

Computation and Language · Computer Science 2024-04-17 Gemma Team , Thomas Mesnard , Cassidy Hardin , Robert Dadashi , Surya Bhupatiraju , Shreya Pathak , Laurent Sifre , Morgane Rivière , Mihir Sanjay Kale , Juliette Love , Pouya Tafti , Léonard Hussenot , Pier Giuseppe Sessa , Aakanksha Chowdhery , Adam Roberts , Aditya Barua , Alex Botev , Alex Castro-Ros , Ambrose Slone , Amélie Héliou , Andrea Tacchetti , Anna Bulanova , Antonia Paterson , Beth Tsai , Bobak Shahriari , Charline Le Lan , Christopher A. Choquette-Choo , Clément Crepy , Daniel Cer , Daphne Ippolito , David Reid , Elena Buchatskaya , Eric Ni , Eric Noland , Geng Yan , George Tucker , George-Christian Muraru , Grigory Rozhdestvenskiy , Henryk Michalewski , Ian Tenney , Ivan Grishchenko , Jacob Austin , James Keeling , Jane Labanowski , Jean-Baptiste Lespiau , Jeff Stanway , Jenny Brennan , Jeremy Chen , Johan Ferret , Justin Chiu , Justin Mao-Jones , Katherine Lee , Kathy Yu , Katie Millican , Lars Lowe Sjoesund , Lisa Lee , Lucas Dixon , Machel Reid , Maciej Mikuła , Mateo Wirth , Michael Sharman , Nikolai Chinaev , Nithum Thain , Olivier Bachem , Oscar Chang , Oscar Wahltinez , Paige Bailey , Paul Michel , Petko Yotov , Rahma Chaabouni , Ramona Comanescu , Reena Jana , Rohan Anil , Ross McIlroy , Ruibo Liu , Ryan Mullins , Samuel L Smith , Sebastian Borgeaud , Sertan Girgin , Sholto Douglas , Shree Pandya , Siamak Shakeri , Soham De , Ted Klimenko , Tom Hennigan , Vlad Feinberg , Wojciech Stokowiec , Yu-hui Chen , Zafarali Ahmed , Zhitao Gong , Tris Warkentin , Ludovic Peran , Minh Giang , Clément Farabet , Oriol Vinyals , Jeff Dean , Koray Kavukcuoglu , Demis Hassabis , Zoubin Ghahramani , Douglas Eck , Joelle Barral , Fernando Pereira , Eli Collins , Armand Joulin , Noah Fiedel , Evan Senter , Alek Andreev , Kathleen Kenealy

Large Language Models (LLMs) are increasingly used for educational support, yet their response quality varies depending on the language of interaction. This paper presents an automated multilingual pipeline for generating, solving, and…

Computation and Language · Computer Science 2025-12-04 Mariam Mahran , Katharina Simbeck

Large Language Models (LLMs) have shown impressive performance on a range of educational tasks, but are still understudied for their potential to solve mathematical problems. In this study, we compare three prominent LLMs, including GPT-4o,…

Artificial Intelligence · Computer Science 2025-07-01 Ruonan Wang , Runxi Wang , Yunwen Shen , Chengfeng Wu , Qinglin Zhou , Rohitash Chandra

The paper surveys automated scientific discovery, from equation discovery and symbolic regression to autonomous discovery systems and agents. It discusses the individual approaches from a "big picture" perspective and in context, but also…

Artificial Intelligence · Computer Science 2026-05-01 Stefan Kramer , Mattia Cerrato , Jannis Brugger , Sašo Džeroski , Ross King

We give a survey of algorithms for computing topological invariants of semi-algebraic sets with special emphasis on the more recent developments in designing algorithms for computing the Betti numbers of semi-algebraic sets. Aside from…

Geometric Topology · Mathematics 2007-09-17 Saugata Basu

Large language models (LLMs) have recently achieved remarkable success in generating rigorous mathematical proofs, with "AI for Math" emerging as a vibrant field of research (Ju et al., 2026). While these models have mastered…

Artificial Intelligence · Computer Science 2026-03-10 Lve Meng , Weilong Zhao , Yanzhi Zhang , Haoxiang Guan , Jiyan He

The developments in Generative AI technologies have paved the way for numerous innovations in different fields. Recently, Generative AI has been proposed as a competitor to AES systems in evaluating student essays automatically. Considering…

Computation and Language · Computer Science 2025-10-20 Enis Oğuz

Recent AI systems have achieved gold-medal-level performance on the International Mathematical Olympiad, demonstrating remarkable proficiency at competition-style problem solving. However, competition mathematics represents only a narrow…

Artificial Intelligence · Computer Science 2026-04-09 Suhaas Garre , Erik Knutsen , Sushant Mehta , Edwin Chen

This paper presents an in-depth analysis of the performance of seven different Large Language Models (LLMs) in solving a diverse set of math advanced calculus problems. The study aims to evaluate these models' accuracy, reliability, and…

Computation and Language · Computer Science 2025-03-07 In Hak Moon

Large Language Models (LLMs) like ChatGPT, DeepSeek and Gemini seem to be increasingly used for knowledge discovery, information retrieval, and knowledge summaries, including for academic topics. This can result in users being misled, such…

Information Retrieval · Computer Science 2026-05-28 Mike Thelwall
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