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Web-based applications such as chatbots, search engines and news recommendations continue to grow in scale and complexity with the recent surge in the adoption of LLMs. Online model selection has thus garnered increasing attention due to…

Machine Learning · Computer Science 2024-03-13 Yu Xia , Fang Kong , Tong Yu , Liya Guo , Ryan A. Rossi , Sungchul Kim , Shuai Li

We study the problem of selecting large language models (LLMs) for user queries in settings where multiple LLM providers submit the cost of solving a query. From the users' perspective, choosing an optimal model is a sequential,…

Computer Science and Game Theory · Computer Science 2026-02-17 Pronoy Patra , Sankarshan Damle , Manisha Padala , Sujit Gujar

Prompt engineering has become central to eliciting the capabilities of large language models (LLMs). At its core lies prompt selection -- efficiently identifying the most effective prompts. However, most prior investigations overlook a key…

Machine Learning · Computer Science 2026-05-15 Donghao Li , Chengshuai Shi , Weijuan Ou , Cong Shen , Jing Yang

The integration of large language models (LLMs) into automated algorithm design has shown promising potential. A prevalent approach embeds LLMs within search routines to iteratively generate and refine candidate algorithms. However, most…

Machine Learning · Computer Science 2026-05-20 Fei Liu , Rui Zhang , Xi Lin , Zhichao Lu , Qingfu Zhang

Cutting-edge Artificial Intelligence (AI) techniques keep reshaping our view of the world. For example, Large Language Models (LLMs) based applications such as ChatGPT have shown the capability of generating human-like conversation on…

Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reasoning tasks. Recent studies have explored fine-tuning Large Language Models (LLMs) with…

Computation and Language · Computer Science 2026-04-10 Shaohua Duan , Pengcheng Huang , Xinze Li , Zhenghao Liu , Xiaoyuan Yi , Yukun Yan , Shuo Wang , Yu Gu , Ge Yu , Maosong Sun

In this paper, we describe the capabilities and constraints of Large Language Models (LLMs) within disparate academic disciplines, aiming to delineate their strengths and limitations with precision. We examine how LLMs augment scientific…

Large language models (LLMs) are at the forefront of transforming numerous domains globally. However, their inclusivity and effectiveness remain limited for non-Latin scripts and low-resource languages. This paper tackles the imperative…

Computation and Language · Computer Science 2025-01-08 Somnath Kumar , Vaibhav Balloli , Mercy Ranjit , Kabir Ahuja , Tanuja Ganu , Sunayana Sitaram , Kalika Bali , Akshay Nambi

The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI's ChatGPT, represents a significant advancement in artificial intelligence. These models, however, bring forth substantial challenges in…

Business Process Management (BPM) aims to improve organizational activities and their outcomes by managing the underlying processes. To achieve this, it is often necessary to consider information from various sources, including unstructured…

Computation and Language · Computer Science 2023-07-20 Michael Grohs , Luka Abb , Nourhan Elsayed , Jana-Rebecca Rehse

The rapid evolution of Large Language Models (LLMs) has markedly expanded their application across diverse domains, transforming how complex problems are approached and solved. Initially conceived to predict subsequent words in texts, these…

Artificial Intelligence · Computer Science 2024-07-11 Sumedh Rasal , E. J. Hauer

Flocking is a behavior where multiple agents in a system attempt to stay close to each other while avoiding collision and maintaining a desired formation. This is observed in the natural world and has applications in robotics, including…

Artificial Intelligence · Computer Science 2024-12-18 Peihan Li , Vishnu Menon , Bhavanaraj Gudiguntla , Daniel Ting , Lifeng Zhou

Mathematical reasoning serves as a cornerstone for assessing the fundamental cognitive capabilities of human intelligence. In recent times, there has been a notable surge in the development of Large Language Models (LLMs) geared towards the…

Computation and Language · Computer Science 2024-09-18 Janice Ahn , Rishu Verma , Renze Lou , Di Liu , Rui Zhang , Wenpeng Yin

Despite their success in many domains, large language models (LLMs) remain under-studied in scenarios requiring optimal decision-making under uncertainty. This is crucial as many real-world applications, ranging from personalized…

Machine Learning · Computer Science 2025-07-15 Allen Nie , Yi Su , Bo Chang , Jonathan N. Lee , Ed H. Chi , Quoc V. Le , Minmin Chen

In machine learning, the notion of multi-armed bandits refers to a class of online learning problems, in which an agent is supposed to simultaneously explore and exploit a given set of choice alternatives in the course of a sequential…

Machine Learning · Computer Science 2021-07-13 Viktor Bengs , Robert Busa-Fekete , Adil El Mesaoudi-Paul , Eyke Hüllermeier

Selecting the best large language model (LLM) for a fixed benchmark is often expensive, since exhaustive evaluation requires running every model on every example. Multi-armed bandit (MAB) algorithms can reduce the number of LLM calls by…

Machine Learning · Computer Science 2026-05-12 Elad Tolochinsky , Yaniv Tenzer , Yaniv Romano

Recently, Large Language Models (LLMs) have shown impressive language capabilities. While most of the existing LLMs have very unbalanced performance across different languages, multilingual alignment based on translation parallel data is an…

Computation and Language · Computer Science 2024-06-19 Shimao Zhang , Changjiang Gao , Wenhao Zhu , Jiajun Chen , Xin Huang , Xue Han , Junlan Feng , Chao Deng , Shujian Huang

Large language models (LLMs) have emerged as powerful tools in chemistry, significantly impacting molecule design, property prediction, and synthesis optimization. This review highlights LLM capabilities in these domains and their potential…

Machine Learning · Computer Science 2024-11-18 Mayk Caldas Ramos , Christopher J. Collison , Andrew D. White

Multi-armed bandit problems are receiving a great deal of attention because they adequately formalize the exploration-exploitation trade-offs arising in several industrially relevant applications, such as online advertisement and, more…

Machine Learning · Computer Science 2013-11-05 Nicolò Cesa-Bianchi , Claudio Gentile , Giovanni Zappella

The evolution of Large Language Models (LLMs) from passive text generators to autonomous, goal-driven systems represents a fundamental shift in artificial intelligence. This chapter examines the emergence of agentic AI systems that…

Artificial Intelligence · Computer Science 2026-01-07 Nadia Sibai , Yara Ahmed , Serry Sibaee , Sawsan AlHalawani , Adel Ammar , Wadii Boulila
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