Search: “research”

arXiv:2608.12962v1 Announce Type: new Abstract: Vertical Federated Learning (VFL) enables organizations holding complementary features of shared entities to collaborate and train models. In this setti

arXiv:2608.13060v1 Announce Type: new Abstract: Machine learning theory studies learning procedures through mathematical setups in which the data model, training protocol, oracle access, loss, metric,

arXiv:2603.20667v2 Announce Type: replace-cross Abstract: Existing prompt-optimization techniques rely on local signals, causing poor generalization across tasks. In addition, they also rely on weak u

arXiv:2608.10431v1 Announce Type: cross Abstract: Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public. How industry practitioners interpret, implemen

arXiv:2608.07250v1 Announce Type: cross Abstract: Confirmed oncogenic microbes contribute significantly to cancer burden. Identifying novel microbial oncogenicity could yield strategies that will redu

arXiv:2511.07322v3 Announce Type: replace-cross Abstract: While LLMs have shown great success in financial tasks like stock prediction and question answering, their application in fully automating Equ

arXiv:2602.13769v3 Announce Type: replace Abstract: Automating heuristic design in complex, experiment-driven domains requires more than iterative mutation of solution algorithms. Current LLM-based ev

arXiv:2607.27209v1 Announce Type: cross Abstract: Peer review at ML conferences increasingly relies on reviewer scores as the primary decision instrument. As submissions have scaled from thousands to

arXiv:2607.25881v1 Announce Type: new Abstract: We investigate how well large language models (LLMs) can assist scientific project planning and proposal evaluation. One-page project plans were indepen

arXiv:2311.18424v3 Announce Type: replace-cross Abstract: Developing artificial intelligence (AI) algorithms for healthcare is a collaborative effort, bringing data scientists, clinicians, patients an

arXiv:2606.31134v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated exceptional capabilities in mathematical reasoning, they frequently produce subtle errors that evad

arXiv:2603.19464v2 Announce Type: replace Abstract: Robotic path planning problems are often NP-hard, and practical solutions typically rely on approximation algorithms with provable performance guara

arXiv:2606.30304v1 Announce Type: cross Abstract: This paper presents preliminary findings from a UKRI-funded Metascience project comparing three LLM-based approaches, GPT-4o, Mistral, and a bespoke a

arXiv:2606.10881v1 Announce Type: new Abstract: Learner agency and autonomy are foundational to personal development, yet a pervasive 'jingle-jangle' fallacy (i.e. identical terms denoting different c

arXiv:2606.09730v1 Announce Type: new Abstract: Large language models are increasingly expected to handle complex, long-horizon real-world tasks whose context demands can grow without bound, yet model

arXiv:2606.03029v1 Announce Type: cross Abstract: A core goal of computational social science is to discover interpretable differences in how language varies across outcomes of interest, such as polit

arXiv:2606.03144v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as self-study assistants in technical disciplines, yet their reliability as mathematical reasoning as

arXiv:2512.23978v2 Announce Type: replace Abstract: Generative artificial intelligence (GenAI) is shifting from conversational assistants toward agentic systems -- autonomous decision-making systems t

arXiv:2605.17000v1 Announce Type: cross Abstract: Optimization of LLM training and inference configurations, such as hyperparameters, data mixtures, and prompts, is critical to performance, but it is

arXiv:2605.00909v1 Announce Type: cross Abstract: The time-consuming formation process critically impacts the longevity of sodium-ion coin cells and End Of Life (EOL) performance. This study aims to o

arXiv:2604.16989v1 Announce Type: new Abstract: We report new results on six problems in mathematics and theoretical computer science, produced with the assistance of Bolzano, an open-source multi-age

arXiv:2604.13654v1 Announce Type: new Abstract: Vision-and-Language Navigation for Unmanned Aerial Vehicles (UAV-VLN) represents a pivotal challenge in embodied artificial intelligence, focused on ena

arXiv:2604.09621v1 Announce Type: new Abstract: We present an agent-driven approach to the construction of parameter inference pipelines for scientific data analysis. Our method leverages a multi-agen

arXiv:2610.12601v1 Announce Type: new Abstract: Prompt optimization is an attractive alternative to reinforcement learning for adapting language-model agents, since it is cheap and produces human-read

arXiv:2609.21859v1 Announce Type: new Abstract: Nearly 90% of drugs entering clinical development ultimately fail, despite billions of dollars in investment. Pharmaceutical companies therefore rely on

arXiv:2609.20519v1 Announce Type: new Abstract: As coding agents move from supervised code completion to unattended, around-the-clock exploration, their work expands from isolated predictions into lon

arXiv:2405.06818v2 Announce Type: replace Abstract: Natural Language Processing (NLP) for Ghana's 73 living indigenous languages remains deeply fragmented, under-resourced, and heavily skewed toward a

arXiv:2609.00018v1 Announce Type: new Abstract: Computer science papers rely heavily on diagrams: architecture drawings, system flowcharts, and pipeline schematics that often carry more information th

arXiv:2508.15757v2 Announce Type: replace Abstract: Configuration optimization remains a critical bottleneck in machine learning, requiring coordinated tuning across model architecture, training strat

arXiv:2608.22582v1 Announce Type: cross Abstract: Large-scale population surveys are essential for generating robust social and scientific insights, yet they face significant challenges, including dec

arXiv:2608.20391v1 Announce Type: new Abstract: Most legal NLP resources draw from federal case law and focus on coarse classification, leaving administrative adjudication, where the vast majority of

arXiv:2608.21107v1 Announce Type: new Abstract: Large Language Models (LLMs) are moving from code completion toward repository-scale agents that retrieve context, edit files, execute tools, and partic

arXiv:2608.19653v1 Announce Type: cross Abstract: Autonomous agents for machine learning experimentation must navigate heterogeneous repositories, repair training pipelines, and evaluate candidate imp

arXiv:2608.13447v1 Announce Type: new Abstract: Academic leagues have become important mechanisms for promoting extracurricular education and strengthening the integration between universities and soc

arXiv:2507.14267v2 Announce Type: replace Abstract: Large language model (LLM) agents can execute long-horizon scientific workflows, but their numerical outputs are difficult to trust: agents lose con

arXiv:2608.07700v1 Announce Type: new Abstract: Translating a natural-language question into a SPARQL query that can be executed against a large knowledge graph requires resolving lexical ambiguity, g

arXiv:2605.12153v2 Announce Type: replace-cross Abstract: We present the Curated Industrial Developer Repository (CIDR), a large-scale dataset of real-world software repositories collected from indust

arXiv:2608.01042v1 Announce Type: cross Abstract: Enterprise AI agents act across many apps whose data changes continuously, so an answer is correct only relative to what data existed and who could se

arXiv:2607.25956v1 Announce Type: new Abstract: Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matche

arXiv:2607.11263v2 Announce Type: replace Abstract: Two competing perspectives on fluid intelligence (gf) measures propose that performance is primarily constrained either by working memory capacity o

arXiv:2607.08700v1 Announce Type: new Abstract: Reinforcement learning increasingly relies on an LLM judge to score each rubric criterion, and that judge acts as the reward model during training. Befo

arXiv:2607.05743v1 Announce Type: cross Abstract: AI coding agents now read repositories, call tools, and execute shell commands with limited human oversight, and a fast-growing body of work studies w

arXiv:2607.02931v1 Announce Type: new Abstract: AI tools are accelerating scientific publication while the systems that review it struggle to keep up, and independent verification of published researc

arXiv:2509.06216v3 Announce Type: replace-cross Abstract: Agentic Software Engineering (SE 3.0) represents a new era where intelligent agents are tasked not with simple code generation, but with achie

arXiv:2606.20677v1 Announce Type: cross Abstract: Computational pathology has advanced rapidly with the emergence of foundation models, yet widespread adoption remains limited by substantial technical

arXiv:2606.11534v1 Announce Type: cross Abstract: Urban heat is amplified by impermeable surfaces and heterogeneous built environments, yet street-level variability remains difficult to quantify becau