Search: “benchmark”

arXiv:2606.24883v1 Announce Type: new Abstract: Artificial intelligence (AI) has achieved remarkable success in medical imaging, but it is widely recognized that these models often perform inconsisten

arXiv:2505.18542v4 Announce Type: replace Abstract: Extracting structured procedural knowledge from unstructured business documents is a critical yet unresolved bottleneck in process automation. While

arXiv:2606.24200v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) in clinical settings increasingly requires multilingual retrieval against predominantly English evidence corpora.

arXiv:2603.16131v2 Announce Type: replace Abstract: The explosive growth of AI research has created unprecedented information overload, increasing the demand for scientific summarization at multiple l

arXiv:2606.22338v1 Announce Type: cross Abstract: Robots deployed in realistic settings will accumulate experience across many sessions and tasks over their deployment. The robot's tasks may often req

arXiv:2606.21949v1 Announce Type: new Abstract: Accurate and comprehensive video captions with consistent subject references are critical for downstream understanding and generation tasks. However, fe

arXiv:2606.20961v1 Announce Type: new Abstract: Continual adaptation is essential for multimodal large language models (MLLMs) deployed across evolving domains, but the state-of-the-art MR-LoRA method

arXiv:2505.17295v2 Announce Type: replace Abstract: We introduce ScanBot, a benchmark for instruction-conditioned, high-precision surface scanning with robot-mounted industrial laser profilers. Unlike

arXiv:2603.06608v2 Announce Type: replace-cross Abstract: The research community lacks a middle ground between StarCraft II full game and its mini-games. The full-game's sprawling state-action space r

arXiv:2405.06995v4 Announce Type: replace-cross Abstract: Automated deception detection is crucial for assisting humans in accurately assessing truthfulness and identifying deceptive behavior. Convent

arXiv:2601.04203v2 Announce Type: replace Abstract: We present FronTalk, a benchmark for front-end code generation that pioneers the study of a unique interaction dynamic: conversational code generati

arXiv:2606.11702v1 Announce Type: cross Abstract: To make clinically grounded decisions, medical AI agents are expected to go beyond simple recognition and be capable of tool retrieval, evidence acqui

arXiv:2606.10066v1 Announce Type: cross Abstract: Medical vision-language models (VLMs) are evaluated on public benchmarks whose images and question-answer pairs have been freely downloadable for year

arXiv:2606.10554v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications that require access to up-to-date knowledge. However, retraining LLM

arXiv:2606.10061v1 Announce Type: new Abstract: Large language models (LLMs) increasingly participate in emotionally sensitive social conversations, where responses may shift from balanced support tow

arXiv:2606.10673v1 Announce Type: cross Abstract: Although some very common test beds exist for assessing the performance of clustering methods, large scale benchmarking is typically limited to relati

arXiv:2606.10852v1 Announce Type: cross Abstract: LLM deception is often evaluated through direct markers such as fabricated claims, explicit lies, or strategic concealment. However, many real-world m

arXiv:2606.11144v1 Announce Type: new Abstract: Resistance to first-line osimertinib in EGFR-mutant non-small-cell lung cancer (NSCLC) is the canonical example of predictable clonal evolution under th

arXiv:2606.11152v1 Announce Type: new Abstract: Multimodal large language models can write code to produce complex programs as well as use programs to do 3D modeling, which opens up a new avenue for 3

arXiv:2606.10255v1 Announce Type: cross Abstract: Cryo-electron tomography (cryoET) has emerged as a powerful tool in structural and cellular biology by enabling direct visualization of macromolecular

arXiv:2606.10394v1 Announce Type: new Abstract: Large language models are increasingly used to power personal agents for everyday applications, but evaluating these agents remains a challenge. Existin

arXiv:2606.11070v1 Announce Type: cross Abstract: Recent advances in reasoning and tool-calling capabilities of large language models (LLMs) have enabled increasingly capable agentic systems. However,

arXiv:2606.10382v1 Announce Type: new Abstract: Real-robot evaluation is essential for understanding whether learned manipulation policies can operate reliably outside curated demonstrations. This nee

arXiv:2603.13431v3 Announce Type: replace-cross Abstract: Computational antibody design has seen rapid methodological progress, with dozens of deep generative methods proposed in the past three years,

arXiv:2606.07542v1 Announce Type: cross Abstract: Generative AI is reshaping healthcare, yet most existing advances rely on hospital-grade devices, which limits their accessibility and potential for h

arXiv:2606.09276v1 Announce Type: new Abstract: Equation discovery aims to automate the discovery of scientific models in the form of mathematical equations from data. Technically, equation discovery

arXiv:2606.08594v1 Announce Type: new Abstract: Deep learning EEG denoising architectures have scaled from tens of thousands to tens of millions of parameters, yet no prior study has isolated model ca

arXiv:2606.09764v1 Announce Type: new Abstract: A useful phone agent needs to be personally intelligent. It should reason over a user's identity, history, and preferences as they exist on the device,

arXiv:2606.08729v1 Announce Type: cross Abstract: Simulation plays a key role in automated robotics research supported by large language models (LLMs). However, existing simulators often require custo

arXiv:2606.07550v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) offers a promising route for developing plasma controllers from historical tokamak data, since online trial-and-er

arXiv:2606.08572v1 Announce Type: new Abstract: While Omni-modal Large Language Models (OLLMs) have demonstrated impressive capabilities in jointly processing audio and visual streams, their ability t

arXiv:2606.07929v1 Announce Type: new Abstract: Large language models (LLMs) are entering clinical practice based on benchmark accuracy that may fail to detect safety-relevant failure modes. Here we p

arXiv:2606.07953v1 Announce Type: new Abstract: Large-scale Visual-Language Models (LVLMs) have achieved remarkable success in natural visual tasks, yet their application to industrial defect detectio

arXiv:2606.09426v1 Announce Type: new Abstract: Computer-use agents (CUAs) increasingly operate in runtimes that combine visual desktop control, command-line execution, code editing, browsers, and ext

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:2512.23128v2 Announce Type: replace-cross Abstract: Web-based agents powered by large language models are increasingly used for tasks such as email management or professional networking. Their r

arXiv:2606.07401v1 Announce Type: new Abstract: Document parsing systems are increasingly deployed in high-stakes, regulated workflows such as mortgage underwriting, financial reporting, supply-chain

arXiv:2510.11974v2 Announce Type: replace-cross Abstract: Cyber Threat Intelligence (CTI) is foundational to modern cybersecurity, enabling organizations to proactively defend against evolving threats

arXiv:2606.05463v1 Announce Type: new Abstract: Patient safety event triage, determining whether a clinical event is reportable under jurisdiction-specific policy, is a high-stakes task typically perf

arXiv:2606.05754v1 Announce Type: cross Abstract: Phase-sensitive optical time-domain reflectometry (phi-OTDR) is widely used in large-scale distributed acoustic sensing (DAS) because it provides dist

arXiv:2606.05949v1 Announce Type: new Abstract: Scientific illustrations are essential tools for communicating research findings, especially in natural science, where they visualize complex concepts a

arXiv:2606.05761v1 Announce Type: cross Abstract: Persistent AI assistants, such as OpenClaw, accumulate large collections of related memories over long-term interactions. As these memories grow, they

arXiv:2606.04874v1 Announce Type: new Abstract: Planning is central to LLM agents: before acting, an agent must decompose goals, select tools, reason over constraints, and decide when a task is infeas

arXiv:2606.04867v1 Announce Type: new Abstract: As AI companion platforms such as Replika and Character.AI rapidly grow, concerns about unsafe human-AI interactions have intensified. This study introd

arXiv:2606.04282v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are predominantly evaluated on free-form vision-language tasks such as visual question answering, captioning, a

arXiv:2603.19225v3 Announce Type: replace-cross Abstract: Real-world financial decision-making is a challenging problem that requires reasoning over heterogeneous signals, including company fundamenta