Search: “agents”

arXiv:2605.28512v1 Announce Type: new Abstract: Self-evolving scientific agents capable of conquering the hard tail of formal mathematics require Compositional Learning Behaviours (CLBs) -- the capaci

arXiv:2605.27631v1 Announce Type: cross Abstract: Code Large Language Models (CLLMs) serve as the core of modern code agents, enabling developers to automate complex software development tasks. In thi

arXiv:2605.28360v1 Announce Type: new Abstract: Automatic prompt optimization (APO) has driven significant gains in LLM-based agentic workflows. However, existing methods treat each task's prompt as a

arXiv:2605.27659v1 Announce Type: cross Abstract: Due to limited resources and public safety concerns, deep reinforcement learning (RL) agents for many cyber-physical systems (e.g., autonomous vehicle

We're selectively releasing the Paris 2.0 weights and partnering with researchers and teams interested in diffusion-based video models, world models, and embodied agents. The model is on Hugging Face:

arXiv:2605.26357v1 Announce Type: new Abstract: A hallmark of intelligence is the ability to adapt in non-stationary environments, yet deep Reinforcement Learning (RL) agents often struggle in such se

Cogent Security Inc., a startup that employs agentic artificial intelligence for vulnerability management, today launched two new platform capabilities aimed at compressing enterprise vulnerability re

arXiv:2605.26316v1 Announce Type: cross Abstract: Controllable and physically grounded egocentric video generation is essential for embodied agents to reason about how their own and others' actions ma

arXiv:2605.26403v1 Announce Type: new Abstract: A long-standing goal of the research community is to develop highly interactive LLM-based dialogue agents. Recent research focuses on optimizing policie

arXiv:2605.27074v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) achieve strong performance on reactive question answering, but real-world streaming assistants require p

arXiv:2605.26667v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on external memory systems to remain consistent across long-horizon interactions, but little empiric

arXiv:2605.26959v1 Announce Type: cross Abstract: MerLean-Prover is an end-to-end Lean4 theorem prover that replaces sorry declarations with kernel-checkable proofs. It is built from three agent types

arXiv:2603.25415v2 Announce Type: replace Abstract: Semantic world models enable embodied agents to reason about objects, relations, and spatial context beyond purely geometric representations. In Org

arXiv:2605.27117v1 Announce Type: new Abstract: AI safety is still largely framed as alignment: training models to follow human preferences, safety policies, and normative constraints. That framing ha

arXiv:2605.27014v1 Announce Type: cross Abstract: Large Language Models (LLMs) have transformed artificial intelligence from primarily generative systems into increasingly capable reasoning agents. Re

arXiv:2605.26340v1 Announce Type: new Abstract: Autonomous research agents produce competitive solutions and professional-looking manuscripts, yet their outputs contain verifiability failures undetect

Dan Goodin / Ars Technica: Starlette, an open-source Python framework underpinning FastAPI, has a vulnerability called BadHost that can allow hackers to bypass authorization — Millions of AI agents an

arXiv:2605.27038v1 Announce Type: new Abstract: Vision-Language Models (VLMs) provide a promising foundation for autonomous driving planning, yet bridging semantic reasoning and precise 3D spatial for

arXiv:2603.23994v2 Announce Type: replace-cross Abstract: Generative optimization uses large language models (LLMs) to iteratively improve artifacts (such as code, workflows or prompts) using executio

arXiv:2601.16578v2 Announce Type: replace Abstract: We present a reproducible benchmark for evaluating sim-to-real transfer of Multi-Agent Reinforcement Learning (MARL) policies for Connected and Auto

KYA is a framework-agnostic trust layer designed for autonomous systems that provides verifiable guarantees, addressing the need for trustworthy and transparent operation of AI agents across different

arXiv:2605.25382v1 Announce Type: new Abstract: Evidence construction systems--chunk retrieval, agent memory, knowledge-graph traversal, and thematic indexing--are evaluated on separate benchmarks wit

arXiv:2601.16091v2 Announce Type: replace-cross Abstract: Clustering is a fundamental problem, aiming to partition a set of elements, like agents or data points, into clusters such that elements in th

arXiv:2605.24543v1 Announce Type: new Abstract: The rapid growth of Electric Vehicle (EV) adoption challenges power distribution networks through peak load spikes, voltage instability, and transformer

arXiv:2602.01576v2 Announce Type: replace-cross Abstract: Mobile Graphical User Interface (GUI) World Models (WMs) offer a promising path for improving mobile GUI agent performance at train- and infer

arXiv:2406.09079v5 Announce Type: replace Abstract: Deep reinforcement learning agents progressively lose representational capacity during training: neurons become dormant, removing active capacity fr

arXiv:2605.25414v1 Announce Type: new Abstract: Distribution shift in imitation learning refers to the problem that the agent cannot plan proper actions for a state that has not been visited during th

arXiv:2605.23908v1 Announce Type: new Abstract: We are in the midst of large-scale industrial and academic efforts to automate the processes of scientific, technological and creative production throug

arXiv:2605.24414v1 Announce Type: new Abstract: We introduce JT-Safe-V2, a large language model designed to advance the safety and trustworthiness of foundation models, extending our previous JT-Safe

arXiv:2605.26012v1 Announce Type: cross Abstract: Deep reinforcement learning (RL) agents commonly rely on high-dimensional neural representations, despite growing evidence that task-relevant value an

The shift to agentic AI creates a new CPU requirement for the AI factory: fast cores, massive memory bandwidth and the ability to sustain high performance when all cores are active. Initial benchmark

arXiv:2605.25789v1 Announce Type: cross Abstract: We study a stochastic multi-armed bandit problem where an agent is granted a free exploration budget before regret accumulates, a setting not captured

ran my first benchmark this weekend (longmemeval) mostly to test activegraph, learned a lot! - this is a stepping stone to show the event based agent system works. the AI convinced me not to start wit

arXiv:2605.24709v1 Announce Type: new Abstract: Streaming reinforcement learning has emerged as an online learning paradigm that conforms to the restrictions of natural learning agents that process da

arXiv:2603.17198v2 Announce Type: replace-cross Abstract: A foundational principle in cognitive science holds that intelligent agents do not learn by storing experiences as isolated instances, but by

arXiv:2605.24703v1 Announce Type: cross Abstract: Large language models (LLMs) and time-series language models (TSLMs) are increasingly applied to time-series question answering (TSQA). Unlike text-on

arXiv:2601.14340v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are widely integrated into interactive systems such as dialogue agents and task-oriented assistants. This growing

arXiv:2605.25832v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as proposal generators for evolutionary robot design, yet most loops remain memoryless: simulator r

arXiv:2605.23262v1 Announce Type: new Abstract: The development of LLM agents has led to a growing body of work on knowledge-work AI, including coding, research, and healthcare. However, current knowl

arXiv:2605.23176v1 Announce Type: new Abstract: Spatiotemporal intelligence in autonomous driving (AD) requires an agent to integrate multi-view observations into a coherent scene representation, main

arXiv:2605.23238v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as economic agents in marketplaces, auctions, and bidding settings. Anticipating their behavior i

arXiv:2605.22880v1 Announce Type: cross Abstract: As large language model (LLM)-based agents increasingly participate in online discourse, red-teaming their capacity to support political influence cam

The post reviews the Hugging Face Reachy Mini robot, praising its build quality, IDE, and developer ecosystem for desktop companion robotics applications. It highlights the robot's support for agentic

arXiv:2605.22872v1 Announce Type: cross Abstract: Experienced physicians develop diagnostic expertise through clinical practice, acquiring not only disease knowledge but also the ability to differenti

arXiv:2605.23108v1 Announce Type: cross Abstract: AI-assisted code review tools typically operate as generic 'expert reviewer' agents, producing homogeneous findings regardless of the analysis type ne

arXiv:2605.22894v1 Announce Type: cross Abstract: Controlling physics-based humanoids from natural-language instructions is a critical step toward general-purpose embodied agents. However, existing me