agents

arXiv:2609.17147v1 Announce Type: cross Abstract: Autonomous racing confronts significant challenges in safely overtaking Opponent Vehicles (OVs) that exhibit uncertain trajectories, stemming from unk

arXiv:2609.17124v1 Announce Type: new Abstract: Offshore maintenance requires operations in the air, the surface, and the subsea domain and include human supervision. This paper presents LOTUSim-Energ

arXiv:2609.16260v1 Announce Type: cross Abstract: Artificial intelligence (AI) poses different levels of risk across sectors, but are these differences reflected in U.S. federal AI governance? To help

MLPerf Inference v6.1 introduced the first agentic workload run on datacenter hardware and evaluated a model with more than one trillion parameters (Kimi K2), setting a new benchmark for scale. The te

arXiv:2609.17306v1 Announce Type: cross Abstract: Multi-agent Systems (MAS) combine multiple model outputs to solve complex reasoning tasks. However, despite rapid growth of available open-source mode

arXiv:2609.16252v1 Announce Type: cross Abstract: Machine-readable models such as SysML v2 are now programmatically accessible, and a growing body of work treats that access as the enabling condition

arXiv:2609.16917v1 Announce Type: cross Abstract: Multilayer Artificial Neural Networks trained via backpropagation are the basic blocks of many, more complex, classification algorithms. Their strengt

arXiv:2609.16984v1 Announce Type: new Abstract: Open-weight language models publish the strings their chat templates use to mark turns, roles and tool results, which the tokenizer maps back to the res

arXiv:2602.10480v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general-purpose reasoning capabilities, yet they frequently hallucinate when used as world models (WMs),

Nice paper discussing context trimming for agents. This is a hot topic at the moment, so it might be worth your time. Context trimming for agents is usually judged by how many tokens it removes. This

arXiv:2609.16186v1 Announce Type: cross Abstract: Autonomous soft-tissue cancer surgery has been limited to interventions on organ surfaces, because current systems cannot perceive and adapt to anatom

arXiv:2609.17302v1 Announce Type: new Abstract: Autonomous robots are increasingly deployed on long duration single- and multi-session missions in dynamic environments, where the ability to identify e

Our framework for reporting model misalignment https://openai.com/index/model-misalignment-reporting-framework/ // if you scrape away all the anthropomorphic language, all the nonsense about thinking,

arXiv:2609.16995v1 Announce Type: new Abstract: Autoresearch agents are reshaping the research ecosystem, but they can also let flawed claims enter the literature at scale. Human advisors catch such i

arXiv:2609.16461v1 Announce Type: cross Abstract: Agentic large language model (LLM) systems rely on long interaction histories to preserve instructions, tool states, intermediate decisions, and unres

arXiv:2607.14097v2 Announce Type: replace Abstract: We introduce RegNetAgents, an AI-oriented multi-agent framework for structured, query-driven regulatory candidate identification across heterogeneou

Rene has a really neat multiplayer agentic experience. I run several agents at once. So I lose track of important conversations throughout the day. Rene pulls conversations from my inbox and manages t

Zack Korman tweeted that rogue AI agents could pose a severe safety threat—“super scary” and potentially lethal—even to entire families. He clarified that the agent‑trace logs from the recent Hugging

arXiv:2609.16662v1 Announce Type: new Abstract: 3D single object tracking (SOT) in LiDAR point clouds is essential for autonomous systems, but remains challenging under sparse and incomplete observati

arXiv:2609.17331v1 Announce Type: new Abstract: Large language model (LLM) agents exhibit strong language-generation and problem-solving capabilities, yet suffer from three structural limitations: per

arXiv:2609.17021v1 Announce Type: new Abstract: Autonomous wheel-loader control requires joint reasoning over task semantics, egocentric vision, proprioception, and 3D scene geometry. We present sensV

arXiv:2607.09493v2 Announce Type: replace Abstract: Agentic LLM systems that generate code through multi-turn tool use face a fundamental context problem: each session starts from zero, discarding the

arXiv:2609.16487v1 Announce Type: new Abstract: We present a framework for evaluating data-science agents on live, continuously updated data using executable ground truth and format-agnostic factoid s

arXiv:2609.17107v1 Announce Type: new Abstract: Generative AI promises natural language access to the massive numerical telemetry of data centers and Industry 4.0 installations, yet text-to-query and

arXiv:2609.17496v1 Announce Type: new Abstract: LLM assistants are widely used for daily social advice, yet evaluating their social reasoning in such consultation settings remains challenging since (i

arXiv:2609.16697v1 Announce Type: cross Abstract: World models connect perception and decision-making in embodied intelligence by maintaining hidden state, anticipating consequences, comparing interve

arXiv:2609.14578v1 Announce Type: new Abstract: Autonomous agents that author building information models need more than access to a host API. They need a representation of what they intended, what a

arXiv:2608.25241v2 Announce Type: replace-cross Abstract: Coding agents increase development velocity but also technical debt. Prior work reports only average effects across adopters, hiding wide diff

arXiv:2609.15389v1 Announce Type: cross Abstract: As artificial intelligence systems increasingly rely on distributed and collaborative training, the energy footprint of these processes becomes a shar

arXiv:2609.13561v1 Announce Type: new Abstract: Efficient utilization of supply chain analytics for decision making remains a significant challenge for planners, as critical tasks such as database que

arXiv:2609.14413v1 Announce Type: cross Abstract: Large language model (LLM)-based database migration is often treated as direct code transformation, although enterprise Oracle systems contain heterog

arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and

arXiv:2609.14872v1 Announce Type: cross Abstract: Agentic serving can consume orders of magnitude more tokens than chatbot workloads, stressing both KV-cache capacity and decode-time bandwidth. Most K

Agents are coming for video production. @PooldayAI is going for this. You prompt it once, and it edits your real footage, picks the right generative model for each task, and checks its own work before

Artificial intelligence agent certification startup Artificial Intelligence Underwriting Company today announced it has raised 40 million in new funding to begin auditing frontier AI models. Until now

arXiv:2609.14756v1 Announce Type: new Abstract: Reliable path tracking is crucial for autonomous underwater vehicles (AUVs) operating in dynamic and uncertain marine environments. However, traditional

arXiv:2609.14824v1 Announce Type: new Abstract: The emergence of large language models (LLMs) and large multimodal models (LMMs) has enabled a new class of agentic systems capable of integrating natur

arXiv:2609.15457v1 Announce Type: new Abstract: Vision-Language Models (VLMs) enable autonomous GUI navigation, but agents still struggle to process and learn from dense, continuous visual histories.

arXiv:2609.13543v1 Announce Type: new Abstract: LLM agents are predominantly benchmarked on short, single-task trajectories, yet real deployments run for hours under contention, surfacing a different

arXiv:2609.15818v1 Announce Type: new Abstract: As AI agents become participants in the development of their successors, they reshape both the production of intelligence and the role of human research

arXiv:2609.15523v1 Announce Type: cross Abstract: Logic attack graphs grounded in scanner output provide explicit and auditable attack path reasoning LLM-based agents lack. Integrating symbolic framew

arXiv:2609.13548v1 Announce Type: new Abstract: Web agents can utilize reusable tools to reduce the cost and latency of low-level browser interaction, but automatically discovered tool collections can

arXiv:2609.14724v1 Announce Type: new Abstract: Inferring intelligence from observable behavior is a foundational challenge in artificial intelligence. We develop a theory of Bayesian intelligence for

arXiv:2609.15624v1 Announce Type: cross Abstract: Researchers assessing competent generative-AI use at work must choose among self-reports, objective tests, and measures of oversight and reliance. We

arXiv:2609.14185v1 Announce Type: cross Abstract: Bird's Eye View (BEV)-based multi-view 3D object detection suffers from challenges of computational complexity, multi-scale feature extraction, and ef

arXiv:2609.15569v1 Announce Type: cross Abstract: Large brains are metabolically costly, and associations with changing environments do not imply they evolved there, as the Cognitive Buffer Hypothesis