Knowledge catalogue
arXiv:2605.00922v1 Announce Type: cross Abstract: There has been intense debate among qualitative researchers about whether generative AI is suitable for qualitative research. In this paper, we summar
arXiv:2609.17846v1 Announce Type: cross Abstract: Autonomous research agents aim to automate scientific workflows, from proposing ideas to conducting experiments and analyzing results. Yet current AI
arXiv:2608.20361v1 Announce Type: cross Abstract: Automated research-idea generation systems built on large language models (LLMs) share a structural weakness: they reduce ideation to free-text recomb
arXiv:2608.12788v1 Announce Type: new Abstract: The rapid advancement of Auto-Research has surfaced a fundamental evaluation challenge: how can we measure the alignment, logical coherence, and evoluti
arXiv:2608.12345v1 Announce Type: new Abstract: Language models are increasingly deployed as co-scientists, yet their ability to uphold research integrity under institutional pressure remains unmeasur
arXiv:2606.07462v1 Announce Type: new Abstract: As foundation models advance and agent scaffolding becomes increasingly sophisticated, agents have demonstrated remarkable proficiency in complex, long-
arXiv:2605.14790v1 Announce Type: cross Abstract: Research idea generation is the innovation-driving step of automated scientific research. Recently, large language models (LLMs) have shown potential
arXiv:2602.01566v2 Announce Type: replace Abstract: Deep research is emerging as a representative long-horizon task for large language model (LLM) agents. However, long trajectories in deep research o
arXiv:2604.15456v1 Announce Type: new Abstract: Trustworthiness and transparency are essential for the clinical adoption of artificial intelligence (AI) in healthcare and biomedical research. Recent d
arXiv:2610.00609v1 Announce Type: new Abstract: Legal research is a core and time-consuming legal workflow. Lawyers must identify controlling authority, verify that it remains valid, reconcile statute
arXiv:2610.01257v1 Announce Type: cross Abstract: Scientific progress emerges from a longitudinal ecosystem in which researchers, institutions, funding agencies, collaboration networks, and the scient
arXiv:2610.00074v1 Announce Type: new Abstract: K-Dense BYOK (bring your own keys) is a free, open-source AI research assistant for scientists in any field that runs on the researcher's own computer.
arXiv:2607.27853v1 Announce Type: new Abstract: Powered by advances in LLMs and autonomous agents, deep research has become one of the most widely adopted agentic products. However, most deep research
arXiv:2605.23448v1 Announce Type: cross Abstract: This work examines an imbalance in artificial intelligence (AI) security research: the field tends to produce more work on attacking AI systems than o
arXiv:2506.11060v2 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code rema
arXiv:2606.18874v2 Announce Type: replace Abstract: AI systems can increasingly automate scientific workflows, but the reasoning that links prior evidence, generated ideas, experiments and final claim
arXiv:2606.25320v1 Announce Type: cross Abstract: Since the 1990s, advancements in big data and information technology have increasingly driven data-centric research in the field of Library and Inform
arXiv:2411.19304v2 Announce Type: replace-cross Abstract: Context: Machine Learning (ML) significantly impacts Software Engineering (SE), but studies mainly focus on practitioners, neglecting research
arXiv:2412.14626v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing
arXiv:2608.14881v1 Announce Type: new Abstract: AI co-scientists that generate hypotheses, retrieve related work, design experiments, execute code, and draft full papers are beginning to change how re
arXiv:2507.04491v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being integrated into psychological and behavioral research as research tools, evaluation targets, hu
arXiv:2607.07779v1 Announce Type: cross Abstract: Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in
arXiv:2604.12198v1 Announce Type: cross Abstract: Recent autonomous LLM agents have demonstrated end-to-end automation of machine-learning research. Real-world physical science is intrinsically harder
arXiv:2604.11184v1 Announce Type: cross Abstract: Context: Software engineering (SE) researchers increasingly study Generative AI (GenAI) while also incorporating it into their own research practices.
arXiv:2604.11261v1 Announce Type: new Abstract: This paper introduces AI as a Research Object (AI-RO), a paradigm for governing the use of generative AI in scientific research. Instead of debating whe
arXiv:2603.11842v2 Announce Type: replace-cross Abstract: The post-ChatGPT surge has rapidly reframed IS research and practice. As organizations and society grapple with GenAI adoption, a body of seco
arXiv:2608.28945v1 Announce Type: new Abstract: Automating alignment research may accelerate progress toward aligned AI, but whether it does is hard to measure. Luckily, many alignment failures, such
arXiv:2608.10740v1 Announce Type: new Abstract: Effective research ideation requires moving beyond a static understanding of prior work to trace how research problems and solutions evolve across the l
arXiv:2606.30246v1 Announce Type: new Abstract: Existing autonomous research agents can support parts of the research process, but most systems still treat research as either an isolated assistant tas
arXiv:2610.06824v2 Announce Type: replace Abstract: We introduce TasteVal, a benchmark to evaluate the experimental research taste of frontier models. We define research taste as the ability to pick i
arXiv:2610.07184v1 Announce Type: cross Abstract: A key challenge in building AI systems for scientific research is enabling extit{scientific exploration}: the systematic process of investigating unkn
arXiv:2601.08536v3 Announce Type: replace Abstract: Deep Research Agents (DRA) aim to help users search the web, synthesize information, and deliver comprehensive investigative reports. Prior benchmar
arXiv:2608.23421v1 Announce Type: new Abstract: Natural Language Processing (NLP) has grown rapidly over the past decade, driven by digital transformation in the Arab world, social media, and large la
arXiv:2506.03218v2 Announce Type: replace-cross Abstract: The EU has become one of the vanguards in regulating the digital age. A particularly important regulation in the Artificial Intelligence (AI)
arXiv:2607.01828v1 Announce Type: cross Abstract: Research in the social sciences has shown that there are gender differences in the selection of research methods, with women often opting for qualitat
arXiv:2607.01833v1 Announce Type: cross Abstract: The global development of Library and Information Science (LIS) is influenced by various factors such as the economy, society, culture, discipline, tr
arXiv:2610.11566v1 Announce Type: new Abstract: Existing Open-Ended Deep Research (OEDR) systems primarily generate reports from scratch, making them inefficient for scenarios where research reports n
arXiv:2609.11970v1 Announce Type: cross Abstract: Qualitative research is widely used in the human and social sciences, characterized by a deep understanding of phenomena through the interpretation of
arXiv:2608.17501v1 Announce Type: new Abstract: Recent efforts toward fully automated AI scientists have demonstrated that language-model agents can generate hypotheses, execute experiments, and draft
arXiv:2608.14354v1 Announce Type: new Abstract: Enabling LLM agents to sustain productive, stable, and goal-aligned research over extended horizons is a central challenge for autonomous machine learni
arXiv:2204.08476v2 Announce Type: replace-cross Abstract: In recent years, with the increase of social investment in scientific research, the number of research results in various fields has increased
arXiv:2607.04439v1 Announce Type: new Abstract: Large language models have made research ideation increasingly accessible, yet effective idea development requires more than generating candidate direct
arXiv:2607.04718v1 Announce Type: new Abstract: Deep research agents decompose open-ended queries into subtasks, retrieve web evidence over multiple rounds, and synthesize long-form reports. This work
arXiv:2606.31081v1 Announce Type: cross Abstract: The present study analyzed over 26,000 research articles published between 1991 and 2021 in twenty-one major LIS (Library and Information Science) jou
arXiv:2606.31651v1 Announce Type: new Abstract: Recent automated research systems show that language-model agents can generate hypotheses, run experiments, and write complete manuscripts, but most evi
arXiv:2605.31468v1 Announce Type: new Abstract: Scientific research has traditionally been human-intensive, requiring researchers to coordinate literature, ideas, experiments, manuscripts, and review
arXiv:2605.27905v1 Announce Type: new Abstract: AI research agents can now generate research ideas, design experiments, run code, and draft papers, raising the possibility of large-scale AI-assisted s
arXiv:2601.22984v2 Announce Type: replace Abstract: Diagnosing failure patterns in Deep Research Agents (DRAs) remains a critical challenge. Existing benchmarks predominantly rely on end-to-end evalua
arXiv:2511.19399v3 Announce Type: replace-cross Abstract: Deep research agents perform multi-step research to produce long-form, well-attributed answers. However, most open deep research agents are tr
arXiv:2605.03042v1 Announce Type: cross Abstract: This report describes ARIS (Auto-Research-in-sleep), an open-source research harness for autonomous research, including its architecture, assurance me
arXiv:2609.38445v1 Announce Type: new Abstract: Frontier LLMs are increasingly used to automate scientific research through iterative search. We distinguish idea-driven search from solution-driven sea
arXiv:2609.10092v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly act as research agents, yet their ability to track shifts in research attention is difficult to evaluate bec
arXiv:2608.08408v1 Announce Type: cross Abstract: Logics of abstraction in computational AI research often push important forms of knowledge and reflection aside: dominant standards of legitimacy sepa
arXiv:2608.09855v1 Announce Type: new Abstract: Autonomous research agents can generate experiments faster than researchers can validate them. Researchers have responded by scaling the proposer and ra
arXiv:2607.27191v1 Announce Type: cross Abstract: Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is t
arXiv:2606.05029v1 Announce Type: cross Abstract: Controlled experiments are the backbone of machine learning research, but at the scale of modern foundation models, they have become prohibitively exp
arXiv:2507.04465v4 Announce Type: replace Abstract: The rapid evolution of deep learning (DL) models and the ever-increasing size of available datasets have raised the interest of the research communi
arXiv:2605.10224v1 Announce Type: new Abstract: Current AI-powered research systems adopt a direct search-then-summarize paradigm that treats hypotheses as end products of scientific discovery. We arg
arXiv:2609.30001v1 Announce Type: new Abstract: Sustaining industrial recommendation research requires using the results of one experiment to decide what to investigate next. We present AgentX-Model,
arXiv:2607.01233v1 Announce Type: cross Abstract: LLMs are increasingly used to brainstorm research ideas, but existing evaluations mostly judge individual ideas by novelty, feasibility, or expert pre