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Agentic AI represents a paradigm shift in enhancing the capabilities of generative AI models. While these systems demonstrate immense potential and power, current evaluation techniques primarily focus on assessing their efficacy in…

Artificial Intelligence · Computer Science 2025-09-30 Hassen Dhrif

Today's conversational agents are restricted to simple standalone commands. In this paper, we present Iris, an agent that draws on human conversational strategies to combine commands, allowing it to perform more complex tasks that it has…

Human-Computer Interaction · Computer Science 2017-07-18 Ethan Fast , Binbin Chen , Julia Mendelsohn , Jonathan Bassen , Michael Bernstein

Traditional goal-oriented dialogue systems rely on various components such as natural language understanding, dialogue state tracking, policy learning and response generation. Training each component requires annotations which are hard to…

The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. Here, we detail the newest…

Many open-domain dialogue systems rely on multiple response generators, any of which can contribute a response to the dialogue in a particular context. Thus the ability to compare potential responses and then select the best plays an…

Computation and Language · Computer Science 2023-02-10 Vrindavan Harrison , Rishi Rajasekaran , Marilyn Walker

LLM agents are increasingly deployed to plan, retrieve, and write with tools, yet evaluation still leans on static benchmarks and small human studies. We present the Agent-Testing Agent (ATA), a meta-agent that combines static code…

Computation and Language · Computer Science 2025-08-26 Sameer Komoravolu , Khalil Mrini

The development of visual analytics (VA) systems has traditionally been a labor-intensive process, balancing design methodologies with complex software engineering practices. In domain-specific fields like urban VA, this challenge is…

Human-Computer Interaction · Computer Science 2026-04-23 Lucas Alexandre , João Rulff , Talisson Souza , Gustavo Moreira , Daniel de Oliveira , Claudio Silva , Fabio Miranda , Marcos Lage

Skele-Code is a natural-language and graph-based interface for building workflows with AI agents, designed especially for less or non-technical users. It supports incremental, interactive notebook-style development, and each step is…

Artificial Intelligence · Computer Science 2026-03-20 Sriram Gopalakrishnan

Despite advances in language and speech technologies, no open-source system enables full speech-to-speech, multi-turn dialogue with integrated tool use and agentic reasoning. We introduce AURA (Agent for Understanding, Reasoning, and…

Artificial Intelligence · Computer Science 2025-07-01 Leander Melroy Maben , Gayathri Ganesh Lakshmy , Srijith Radhakrishnan , Siddhant Arora , Shinji Watanabe

We describe 'staq', a full-stack quantum processing toolkit written in standard C++. 'staq' is a quantum compiler toolkit, comprising of tools that range from quantum optimizers and translators to physical mappers for quantum devices with…

Quantum Physics · Physics 2020-08-07 Matthew Amy , Vlad Gheorghiu

API testing has increasing demands for software companies. Prior API testing tools were aware of certain types of dependencies that needed to be concise between operations and parameters. However, their approaches, which are mostly done…

Software Engineering · Computer Science 2024-07-16 Tri Le , Thien Tran , Duy Cao , Vy Le , Tien Nguyen , Vu Nguyen

We present SDialog, an MIT-licensed open-source Python toolkit that unifies dialog generation, evaluation and mechanistic interpretability into a single end-to-end framework for building and analyzing LLM-based conversational agents. Built…

AI-driven autoformalization of mathematics is advancing rapidly. However, the type checker of a proof assistant guarantees only the logical correctness of proofs; it does not verify whether propositions and definitions faithfully capture…

Human-Computer Interaction · Computer Science 2026-04-21 Banri Yanahama , Akiyoshi Sannai

Recent advancements in Large Language Models (LLMs) have substantially evolved Multi-Agent Systems (MASs) capabilities, enabling systems that not only automate tasks but also leverage near-human reasoning capabilities. To achieve this,…

Artificial Intelligence · Computer Science 2025-02-27 Humza Sami , Mubashir ul Islam , Samy Charas , Asav Gandhi , Pierre-Emmanuel Gaillardon , Valerio Tenace

This paper presents ADAMANT, a set of software modules that provides grasp planning capabilities to an existing robot planning and control software framework. Our presented work allows a user to adapt a manipulation task to be used under…

Robotics · Computer Science 2022-09-16 Ana Huamán Quispe , Stephen Hart , Seth Gee , Robert R. Burridge

Small-angle neutron scattering (SANS) data reduction at user facilities follows a largely repetitive workflow. Runs are first classified in the catalog and matched to transmission, background, and empty-beam references within the same…

Instrumentation and Detectors · Physics 2026-05-04 Changwoo Do

We describe an intelligent assistant based on mining existing software repositories to help the developer interactively create checkable specifications of code. To be most useful we apply this at the subsystem level, that is chunks of code…

Software Engineering · Computer Science 2022-09-21 Steven P. Reiss

We present GR-NLP-TOOLKIT, an open-source natural language processing (NLP) toolkit developed specifically for modern Greek. The toolkit provides state-of-the-art performance in five core NLP tasks, namely part-of-speech tagging,…

In this paper, we propose a novel end-to-end approach for AI-assisted code completion called Pythia. It generates ranked lists of method and API recommendations which can be used by software developers at edit time. The system is currently…

Software Engineering · Computer Science 2019-12-03 Alexey Svyatkovskiy , Ying Zhao , Shengyu Fu , Neel Sundaresan

As Large Language Models (LLMs) become ubiquitous across various scientific domains, their lack of ability to perform complex tasks like running simulations or to make complex decisions limits their utility. LLM-based agents bridge this gap…

Computation and Language · Computer Science 2026-01-21 Anurag Acharya , Timothy Vega , Rizwan A. Ashraf , Anshu Sharma , Derek Parker , Robert Rallo
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