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Large language models (LLMs) have recently driven striking performance improvements across a range of natural language processing tasks. The factual knowledge acquired during pretraining and instruction tuning can be useful in various…

Computation and Language · Computer Science 2023-10-10 Xuming Hu , Junzhe Chen , Xiaochuan Li , Yufei Guo , Lijie Wen , Philip S. Yu , Zhijiang Guo

This survey reviews works in which language models (LMs) are augmented with reasoning skills and the ability to use tools. The former is defined as decomposing a potentially complex task into simpler subtasks while the latter consists in…

Large language models (LLMs) offer promise in generating educational content, providing instructor feedback, and reducing teacher workload on assessments. While prior studies have focused on studying LLM-powered learning analytics, limited…

Computation and Language · Computer Science 2024-11-08 Anand Syamkumar , Nora Tseng , Kaycie Barron , Shanglin Yang , Shamya Karumbaiah , Rheeya Uppal , Junjie Hu

Large language models are powerful but often limited by high computational cost, privacy concerns, and English-centric training. Recent progress demonstrates that small, efficient models with around one billion parameters can deliver strong…

Computation and Language · Computer Science 2025-12-16 Anna Aksenova , Boris Zverkov , Nicola Dainese , Alexander Nikitin , Pekka Marttinen

In many scientific fields, large language models (LLMs) have revolutionized the way text and other modalities of data (e.g., molecules and proteins) are handled, achieving superior performance in various applications and augmenting the…

Computation and Language · Computer Science 2024-10-01 Yu Zhang , Xiusi Chen , Bowen Jin , Sheng Wang , Shuiwang Ji , Wei Wang , Jiawei Han

Clinical decision-making is a dynamic, interactive, and cyclic process where doctors have to repeatedly decide on which clinical action to perform and consider newly uncovered information for diagnosis and treatment. Large Language Models…

Computation and Language · Computer Science 2026-03-03 David Bani-Harouni , Chantal Pellegrini , Ege Özsoy , Nassir Navab , Matthias Keicher

We present an approach for automatically generating and testing, in silico, social scientific hypotheses. This automation is made possible by recent advances in large language models (LLM), but the key feature of the approach is the use of…

General Economics · Economics 2024-04-26 Benjamin S. Manning , Kehang Zhu , John J. Horton

Despite rapid progress in large language models (LLMs), their performance on a vast majority of languages remains unsatisfactory. In this paper, we study building language-specific LLMs by adapting monolingual and multilingual LLMs. We…

Computation and Language · Computer Science 2024-10-31 Atula Tejaswi , Nilesh Gupta , Eunsol Choi

Despite their strong performance, large language models (LLMs) face challenges in real-world application of lexical simplification (LS), particularly in privacy-sensitive and resource-constrained environments. Moreover, since vulnerable…

Computation and Language · Computer Science 2025-09-30 Akio Hayakawa , Stefan Bott , Horacio Saggion

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence. The application of LLMs extends beyond conventional…

As Large Language Models (LLMs) become increasingly integrated into our daily lives, the potential harms from deceptive behavior underlie the need for faithfully interpreting their decision-making. While traditional probing methods have…

Machine Learning · Computer Science 2024-11-08 Anthony Costarelli , Mat Allen , Severin Field

Large Language Models (LLMs) are important tools for reasoning and problem-solving, while they often operate passively, answering questions without actively discovering new ones. This limitation reduces their ability to simulate human-like…

Computational Engineering, Finance, and Science · Computer Science 2025-09-26 Hong Su

Existing large language models (LLMs) evaluation methods typically focus on testing the performance on some closed-environment and domain-specific benchmarks with human annotations. In this paper, we explore a novel unsupervised evaluation…

Computation and Language · Computer Science 2025-02-24 Kun-Peng Ning , Shuo Yang , Yu-Yang Liu , Jia-Yu Yao , Zhen-Hui Liu , Yong-Hong Tian , Yibing Song , Li Yuan

The limited reasoning capabilities of small language models (SLMs) cast doubt on their suitability for tasks demanding deep, multi-step logical deduction. This paper introduces a framework called Small Reasons, Large Hints (SMART), which…

Computation and Language · Computer Science 2025-06-03 Yujin Kim , Euiin Yi , Minu Kim , Se-Young Yun , Taehyeon Kim

Recent work investigates whether LMs learn human-like linguistic generalizations and representations from developmentally plausible amounts of data. Yet, the basic linguistic units processed in these LMs are determined by subword-based…

Computation and Language · Computer Science 2025-01-07 Bastian Bunzeck , Daniel Duran , Leonie Schade , Sina Zarrieß

Large Language Models (LLMs) have reshaped our world with significant advancements in science, engineering, and society through applications ranging from scientific discoveries and medical diagnostics to Chatbots. Despite their ubiquity and…

Artificial Intelligence · Computer Science 2025-08-26 Kushal Raj Bhandari , Pin-Yu Chen , Jianxi Gao

Language models (LMs) are powerful tools for natural language processing, but they often struggle to produce coherent and fluent text when they are small. Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can…

Computation and Language · Computer Science 2023-05-26 Ronen Eldan , Yuanzhi Li

Human language offers a powerful window into our thoughts -- we tell stories, give explanations, and express our beliefs and goals through words. Abundant evidence also suggests that language plays a developmental role in structuring our…

Computation and Language · Computer Science 2022-05-13 Katherine M. Collins , Catherine Wong , Jiahai Feng , Megan Wei , Joshua B. Tenenbaum

The development of highly fluent large language models (LLMs) has prompted increased interest in assessing their reasoning and problem-solving capabilities. We investigate whether several LLMs can solve a classic type of deductive reasoning…

Computation and Language · Computer Science 2024-04-16 Spencer M. Seals , Valerie L. Shalin

The field of AI research is advancing at an unprecedented pace, enabling automated hypothesis generation and experimental design across diverse domains such as biology, mathematics, and artificial intelligence. Despite these advancements,…

Machine Learning · Computer Science 2025-10-07 Yaowenqi Liu , Bingxu Meng , Rui Pan , Yuxing Liu , Jerry Huang , Jiaxuan You , Tong Zhang