Search: “copilot”

arXiv:2607.05125v1 Announce Type: cross Abstract: This paper presents an exploratory evaluation of how increasing levels of AI autonomy affect software development productivity, requirement adherence,

arXiv:2605.29018v1 Announce Type: new Abstract: Although a growing body of research has begun to describe user--LLM interactions, the picture it paints is largely static; little is known about how ind

arXiv:2605.04171v1 Announce Type: new Abstract: Large Language models (LLMs) show extraordinary abilities, but they are still prone to hallucinations, especially when we use them for generating Academ

arXiv:2605.02491v1 Announce Type: cross Abstract: Modern searches for physics beyond the Standard Model produce rapidly expanding literature containing heterogeneous information, including textual ana

arXiv:2604.19689v1 Announce Type: new Abstract: Understanding artworks requires multi-step reasoning over visual content and cultural, historical, and stylistic context. While recent multimodal large

arXiv:2604.10721v1 Announce Type: cross Abstract: Natural-language Guided Cross-view Geo-localization (NGCG) aims to retrieve geo-tagged satellite imagery using textual descriptions of ground scenes.

arXiv:2609.29947v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive performance on a wide range of generative tasks. Yet their probabilistic nature makes them, in isolat

arXiv:2609.22510v1 Announce Type: cross Abstract: As LLM applications integrate with external tools, they are increasingly exposed to indirect prompt injection (IPI), where adversarial instructions ar

arXiv:2609.20218v1 Announce Type: cross Abstract: Large language models can label a tabular row from a plain-English description with no training - a capability now shipping in mainstream spreadsheet

arXiv:2609.19151v1 Announce Type: new Abstract: Generative AI (GenAI) applications have achieved rapid consumer adoption, yet little large-scale research examines user-perceived quality, trust, and ad

arXiv:2609.16856v1 Announce Type: cross Abstract: English Wikipedia is one of the largest examples of collective intelligence on the Web, sustained not only by article production but also by volunteer

arXiv:2511.20109v2 Announce Type: replace Abstract: Climate science demands automated workflows to transform comprehensive questions into data-driven statements across massive, heterogeneous datasets.

arXiv:2609.11321v1 Announce Type: new Abstract: Artificial intelligence is changing both software production and the economics of software-based business models. Classical technology due diligence mai

arXiv:2609.11060v1 Announce Type: new Abstract: Persistent memory is entering production-oriented agent platforms to help long-horizon agents accumulate experience across sessions. Yet a post-task cur

arXiv:2609.04898v1 Announce Type: cross Abstract: Repository-scale refactoring requires coding agents to propagate a single change across many interdependent files without altering program behavior, y

arXiv:2511.15755v3 Announce Type: replace Abstract: Large language models (LLMs) promise to accelerate incident response in production systems, yet single-agent approaches generate vague, unusable rec

arXiv:2608.29204v1 Announce Type: cross Abstract: Generative AI-based software engineering agents are becoming routine contributors to real-world software projects. On GitHub, developers can assign ta

arXiv:2602.18492v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are now good enough at coding that developers can describe intent in plain language and let the tool produce the

arXiv:2608.16318v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence (GenAI) have substantially improved the ability of large language models (LLMs) to generate and

arXiv:2608.13730v1 Announce Type: cross Abstract: Empirical reports on the true cost of AI-intensive software development remain scarce, and the few that exist are easy to get wrong in ways that never

arXiv:2608.12352v1 Announce Type: cross Abstract: AI governance frameworks can be known, used, and implemented in form without becoming governance in practice. This paper examines that problem through

arXiv:2608.05144v1 Announce Type: new Abstract: Long-horizon reasoning requires an agentic runtime that can persist when evidence supports its current approach and pivot when measurements reveal failu

arXiv:2512.02567v2 Announce Type: replace-cross Abstract: The advent of strong generative AI has a considerable impact on various software engineering tasks such as code repair, test generation, or la

arXiv:2608.01004v1 Announce Type: new Abstract: Platform teams hosting agent-extensibility surfaces face a regression-economics paradox: every onboarding customer ships an evaluation set tuned to thei

arXiv:2607.25992v1 Announce Type: cross Abstract: Recently, memory management has become a key infrastructure for LLM-based agents, as it directly affects long-horizon reasoning, personalized response

arXiv:2607.24589v1 Announce Type: new Abstract: The development of the Innovative Ecosystem (IE) presents a new paradigm for economic integration, collaborative advancement, and shared achievements. T

arXiv:2607.19409v1 Announce Type: new Abstract: Recent advances in large language models have accelerated deployment of agentic systems in operational finance. Existing benchmarks emphasize measuring

arXiv:2607.12823v1 Announce Type: new Abstract: Interaction with AI agents has become one of the most frequent activities of everyday digital life. Whether conversing with an assistant, working with a

arXiv:2607.08180v1 Announce Type: cross Abstract: The rise of LLM-based agents with reasoning, summarization, and memory capabilities has created a new threat surface for online content that conventio

arXiv:2607.03968v1 Announce Type: cross Abstract: Large language models are increasingly deployed as IDE-integrated coding agents that decompose tasks, generate and edit files, run code, and refine ou

arXiv:2607.03451v1 Announce Type: cross Abstract: While skill optimization for autonomous agents has gained traction, existing methods rely on complex pipelines. This leaves a fundamental question una

arXiv:2606.28430v1 Announce Type: cross Abstract: Benchmarks are widely used to evaluate task completion by Large Language Models (LLMs), but this approach has accumulated construction-validity proble

arXiv:2606.28333v1 Announce Type: cross Abstract: egin{quote} The biases in Large Language Models' (LLMs) outputs remain inadequately theorised, particularly from the perspective of the Global South.

arXiv:2606.24834v1 Announce Type: new Abstract: LLM-based dialogue assistants have become mainstream tools for software developers, yet current evaluation benchmarks focus exclusively on functional co

arXiv:2606.04035v1 Announce Type: cross Abstract: We present a systematic study of domain-dependent safety behavior in open-weight LLMs: 7 standardized experiments across 7 ethical domains, testing 5

arXiv:2605.30712v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong capabilities in reasoning, tool use, and multi-step interaction, but they often solve tasks from scr

arXiv:2510.04704v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown promising potential in scientific research, enabling tasks ranging from knowledge retrieval to propert

arXiv:2605.24421v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as analyst assistants in security operations centers (SOCs), where they ingest log and alert data t

arXiv:2605.17106v1 Announce Type: new Abstract: Production LLM deployments increasingly maintain heterogeneous model pools spanning order-of-magnitude cost differences. Existing routers make binary st

arXiv:2605.13532v1 Announce Type: new Abstract: As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors. To that end, this paper examines u

arXiv:2605.03808v1 Announce Type: cross Abstract: Agentic data science (ADS) systems are rapidly improving their capability to autonomously analyze, fit, and interpret data, potentially moving towards

arXiv:2604.18658v1 Announce Type: cross Abstract: Existing AI agent safety benchmarks focus on generic criminal harm (cybercrime, harassment, weapon synthesis), leaving a systematic blind spot for a d

arXiv:2604.12986v1 Announce Type: cross Abstract: Autonomous AI agents are rapidly transitioning from experimental tools to operational infrastructure, with projections that 80% of enterprise applicat

arXiv:2604.09388v1 Announce Type: cross Abstract: AI coding tools are widely adopted, but most teams plateau at prompt-and-review without a framework for systematic progression. This paper presents th