Search: “agents”

arXiv:2605.18396v1 Announce Type: new Abstract: Video generation models produce visually compelling results but systematically violate physical commonsense -- on VideoPhy-2, the best model achieves on

arXiv:2605.18150v1 Announce Type: new Abstract: Diffusion models (DMs) are widely used for text-to-image generation, but their strong generative capabilities also raise concerns about unsafe or undesi

arXiv:2605.16207v1 Announce Type: new Abstract: Effective tutoring requires distinguishing optimal, valid but suboptimal, and incorrect student solutions, a distinction central to intelligent tutoring

arXiv:2605.15221v1 Announce Type: cross Abstract: AlphaEvolve and FunSearch have demonstrated the potential of combining large language models (LLMs) with evolutionary search for automated algorithm d

arXiv:2604.05966v2 Announce Type: replace Abstract: Financial reporting systems increasingly leverage Large Language Models (LLMs) to extract and summarize corporate disclosures. However, most existin

arXiv:2605.15338v1 Announce Type: cross Abstract: Large language models are increasingly augmented with persistent memory, allowing assistants to store user-specific information across sessions for pe

arXiv:2409.03897v3 Announce Type: replace Abstract: Large-scale multi-agent systems are often deployed across wide geographic areas, where agents interact with heterogeneous environments. There is an

arXiv:2605.16079v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have shown significant progress in video understanding, yet they face substantial challenges in tasks requiring p

arXiv:2605.14163v1 Announce Type: new Abstract: Can a committee of weak reasoning-model calls reach the performance of much stronger models? We study verifier-backed committee search as inference-time

arXiv:2605.14141v1 Announce Type: new Abstract: We study learning when the learned object is executable solver code rather than a predictor. In this setting, correctness is not enough: two solvers may

arXiv:2605.14120v1 Announce Type: cross Abstract: Geospatial foundation models compress multispectral observations into dense embeddings increasingly used in natural-language environmental reasoning s

arXiv:2605.14283v1 Announce Type: cross Abstract: Watermarking techniques for large language models (LLMs), which encode hidden information in the output so its source can be verified, have gained sig

arXiv:2605.13542v1 Announce Type: new Abstract: Intensive care units (ICU) generate long, dense and evolving streams of clinical information, where physicians must repeatedly reassess patient states u

arXiv:2605.13414v1 Announce Type: new Abstract: Deploying language models as autonomous agents requires more than per-task accuracy: when an agent faces a queue of problems under a finite token budget

arXiv:2605.12497v1 Announce Type: new Abstract: Visual perception connects high-level semantic understanding to pixel-level perception, but most existing settings assume that the decisive evidence for

arXiv:2602.02799v2 Announce Type: replace Abstract: Building agents that can perform new skills by composing existing skills is a long-standing goal of AI agent research. Towards this end, we investig

arXiv:2605.11363v1 Announce Type: cross Abstract: Presentation generation is moving beyond static slide creation toward end-to-end presentation video generation with research grounding, multimodal med

arXiv:2605.11374v1 Announce Type: cross Abstract: Test-time compute is widely believed to benefit only large reasoning models. We show it also helps small embedding models. Most modern embedding check

arXiv:2605.08480v1 Announce Type: new Abstract: Individuals with Alzheimer's disease (AD) and Alzheimer's disease-related dementia (ADRD) experience memory and thinking changes that impact their abili

arXiv:2605.10876v1 Announce Type: cross Abstract: Recent advances in machine learning and large-scale biological data collections have revived the prospect of building a virtual cell, a computational

arXiv:2605.09395v1 Announce Type: new Abstract: In this paper, we propose the first VLnderline{extbf{M}} nderline{extbf{a}}gentic nderline{extbf{r}}easoning framework for few-nderline{extbf{s}}hot mul

arXiv:2605.09217v1 Announce Type: new Abstract: For AI systems to be useful to humans, they must understand and act in accordance with our values and preferences. Since specifying preferences is a har

arXiv:2605.08583v1 Announce Type: new Abstract: Large language models are increasingly used in scientific writing, yet they can fabricate citation-shaped references that appear plausible but fail bibl

arXiv:2605.06924v1 Announce Type: cross Abstract: Synthesizing consistent and coherent long video remains a fundamental challenge. Existing methods suffer from semantic drift and narrative collapse ov

arXiv:2605.07646v1 Announce Type: cross Abstract: While explicit reasoning trajectories enhance model interpretability, existing paradigms often rely on monolithic chains that lack intermediate verifi

arXiv:2605.07039v1 Announce Type: new Abstract: Large language models have become drivers of evolutionary search, but most systems rely on a fixed, prompt-elicited policy to sample next candidates. Th

arXiv:2605.03648v1 Announce Type: new Abstract: To understand complex system dynamics in dairy farming, it is essential to use modeling tools that capture farm heterogeneity, social interactions, and

arXiv:2605.04003v1 Announce Type: cross Abstract: High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledg

arXiv:2605.04870v1 Announce Type: new Abstract: Video text-based visual question answering (Video TextVQA) aims to answer questions by reasoning over visual textual content appearing in videos. Despit

arXiv:2605.02910v1 Announce Type: cross Abstract: Recent advances in large language models have led to strong performance on reasoning and environment-interaction tasks, yet their ability for creative

arXiv:2605.03476v1 Announce Type: new Abstract: Discharge summaries require extracting critical information from lengthy electronic health records (EHRs), a process that is labor-intensive when perfor

arXiv:2604.25000v2 Announce Type: replace Abstract: Recent work has framed intelligence in verifiable tasks as reducing time-to-solution through learned structure and test-time search, while systems w

arXiv:2408.01055v2 Announce Type: replace-cross Abstract: Self-healing systems have long been a focus of research, aiming to enable software to recover from unexpected runtime errors without human int

arXiv:2605.02651v1 Announce Type: cross Abstract: Scientific peer review increasingly struggles to assess reproducibility at the scale and complexity of modern research output. Evaluating reproducibil

arXiv:2605.00876v1 Announce Type: cross Abstract: Vision-language models (VLMs) read an image and produce text in a single forward pass, whereas radiologists typically inspect an image several times a

arXiv:2605.00845v1 Announce Type: cross Abstract: Knowledge Graph Question Answering (KGQA) has advanced through structured query generation, yet most efforts target RDF/SPARQL, leaving Cypher and pro

arXiv:2605.01386v1 Announce Type: new Abstract: Large Language Models (LLMs) lack persistent memory for long-term personalized conversations. Existing graph-based memory systems suffer from informatio

arXiv:2605.01041v1 Announce Type: cross Abstract: In the envisioned future dense urban airspace, multiple companies will operate heterogeneous fleets of small unmanned aerial systems (sUASs), where ea

arXiv:2604.28001v1 Announce Type: new Abstract: Integrating multimodal foundation models into enterprise ecosystems presents a fundamental software architecture challenge. Architects must balance comp

arXiv:2604.26959v1 Announce Type: cross Abstract: Integrating large language models (LLMs) into patient-facing healthcare systems offers significant potential to improve access to medical information.

arXiv:2601.10702v2 Announce Type: replace-cross Abstract: Deploying large language models in long-horizon, goal-oriented interactions remains challenging because similar entities and facts recur under

arXiv:2604.27616v1 Announce Type: new Abstract: People commonly leverage structured content to accelerate knowledge acquisition and research problem solving. Among these, roadmaps guide researchers th

arXiv:2604.26703v1 Announce Type: cross Abstract: Standard density functional theory (DFT) routinely misclassifies the electronic ground state of correlated and structurally complex compounds, predict

arXiv:2604.25120v1 Announce Type: new Abstract: We study clinical trial table reasoning, where answers are not directly stored in visible cells but must be reasoned from semantic understanding through

arXiv:2604.25914v1 Announce Type: new Abstract: Real-world data visualization (DV) requires native environmental grounding, cross-platform evolution, and proactive intent alignment. Yet, existing benc

arXiv:2511.16518v2 Announce Type: replace-cross Abstract: We open-source MiMo-Embodied, the first cross-embodied foundation model to successfully integrate and achieve state-of-the-art performance in