Search: “agents”

arXiv:2605.27559v1 Announce Type: cross Abstract: Multi-stage LLM pipelines that perform multi-agent debate, intrinsic self-correction, or retrieval-augmented verification exhibit puzzling aggregate b

arXiv:2605.28751v1 Announce Type: cross Abstract: Linear interpolation between fine-tuned checkpoints has been shown to trace the Pareto front between competing objectives, but whether extrapolative w

arXiv:2512.20780v3 Announce Type: replace Abstract: Recent work has explored the use of large language models (LLMs) to generate tutoring responses in mathematics, yet it remains unclear how closely t

arXiv:2605.28232v1 Announce Type: new Abstract: Occupant comfort and grid-aware energy efficiency are competing objectives whose joint optimization depends critically on how reward functions are speci

arXiv:2605.27532v1 Announce Type: new Abstract: Emergent communication enables partially observant Autonomous Mobile Robots (AMRs) to coordinate effectively in decentralized multi-agent reinforcement

arXiv:2604.08304v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external knowledge, but this access path also introduces securi

arXiv:2605.27599v1 Announce Type: cross Abstract: Agentic AI workloads - where a single user goal triggers multi-step orchestration, tool calls, retries, and failure recovery - are being targeted for

arXiv:2605.28065v1 Announce Type: new Abstract: AI agents are increasingly useful for biological data analysis, but existing benchmarks mostly test broad biological knowledge, executable workflows, or

arXiv:2605.27882v1 Announce Type: cross Abstract: LLM-based agents score well on search benchmarks, yet real users consistently find results unsatisfying, revealing a persistent evaluation-experience

arXiv:2605.27082v1 Announce Type: new Abstract: Biomedical discovery often requires connecting broad biomedical knowledge with specific experimental or clinical data. Background knowledge suggests rel

arXiv:2605.27076v1 Announce Type: cross Abstract: In many multi-agent applications, tasks yield rewards only when executed by a coalition meeting an unknown size threshold; otherwise, feedback is full

arXiv:2605.26451v1 Announce Type: cross Abstract: Producing presentation slides automatically entails coordinating narrative structure with page-level graphic design under strict spatial constraints.

arXiv:2603.11790v3 Announce Type: replace Abstract: Symmetry-based disentangled representation learning leverages the group structure of environment transformations to uncover the latent factors of va

For future-proof, build AI that's composable. Regardless of what you use, all these should be composable, iterative, and customizable: - LLMs - Evals - Automations - MCP/CLI tools - Skills/Memory/Cont

arXiv:2509.21552v2 Announce Type: replace-cross Abstract: Graphical User Interface (GUI) grounding is commonly framed as a coordinate prediction task -- given a natural language instruction, generate

arXiv:2605.26147v1 Announce Type: new Abstract: Human decision-making is sequential and uncertainty-aware, yet standard neural networks often rely on static, dense forward computation with limited vis

arXiv:2602.04397v2 Announce Type: replace-cross Abstract: We study a setting in which two players play a (possibly approximate) Nash equilibrium of a bimatrix game, while a learner observes only their

arXiv:2602.03545v2 Announce Type: replace Abstract: Evaluating AI systems that interact with humans requires understanding their behavior across diverse user populations, but collecting representative

arXiv:2605.26543v1 Announce Type: new Abstract: Polymer discovery is central to fields ranging from energy storage to biomedicine, but it is hindered by an astronomically large chemical design space a

arXiv:2605.26891v1 Announce Type: new Abstract: This paper presents a multilingual customer service self-help corpus comprising 1,122 manually validated documents in Finnish, Danish, Norwegian, and Sw

arXiv:2605.26155v1 Announce Type: cross Abstract: Guided Soft Actor-Critic (GSAC) distills knowledge from a privileged full-state teacher to a partial-observation student for autonomous driving, but u

Not content with its push into autonomous artificial intelligence workers, WisdomAI Inc. is bringing its comprehensive analytics capabilities to third-party software-as-a-service platforms with today’

@yoheinakajima is genuinely the coolest power user you can have as an ai company got to talk to him the other day about how he's using cofounder and left thinking about how i coddle my agents too much

arXiv:2512.05765v2 Announce Type: replace Abstract: In this paper we argue that influential critiques dismissing Large Language Models (LLMs) as a dead end for AGI misidentify the bottleneck: they con

arXiv:2605.24125v1 Announce Type: new Abstract: We consider the problem of combining potential field and ergodic search on multi-robot systems. Traditional ergodic search algorithms use metrics for er

arXiv:2605.24423v1 Announce Type: new Abstract: In-Context Reinforcement Learning (ICRL) has enabled foundation agents to adapt instantaneously to novel tasks, yet its efficacy in Ad-Hoc Teamwork (AHT

arXiv:2605.11359v2 Announce Type: replace Abstract: Scientific data processing often requires task-specific algorithms or AI models, creating a barrier for domain scientists who need to analyze their

arXiv:2605.24761v1 Announce Type: cross Abstract: We propose Drift-Resistant Navigation World Model, a generative model that mitigates both perceptual drift and geometric drift in conventional rollout

arXiv:2605.23955v1 Announce Type: new Abstract: Deploying machine learning in regulated financial environments -- credit risk, fraud detection, and anti-money laundering -- exposes critical vulnerabil

arXiv:2605.24784v1 Announce Type: new Abstract: Domain scientists increasingly develop Python scripts to analyze satellite imagery but they lack scalability to large-scale data. This paper demonstrate

Over the last 25 years of building Google’s global network, we’ve navigated major architectural eras — from the Internet, to streaming, and the cloud. Today, we are squarely in the midst of a fourth:

arXiv:2605.23952v1 Announce Type: new Abstract: Artificial agents now generate behavior rich enough to invite trust, surprise, and concern, yet our evaluation tools still privilege capability scores o

arXiv:2605.23964v1 Announce Type: cross Abstract: The growing share of Renewable Energy Sources (RES) in modern power systems increases both grid imbalances and frequency deviations, reinforcing the n

arXiv:2502.21297v2 Announce Type: replace Abstract: Persuasive dialogue is central to human communication, yet existing datasets often rely on a single language model generating both roles, producing

arXiv:2605.23187v1 Announce Type: new Abstract: Existing object navigation benchmarks usually tell an embodied agent which object category to find, such as microwave or chair. Human-facing embodied AI

arXiv:2511.02239v2 Announce Type: replace-cross Abstract: Learning generalizable policies for robotic manipulation increasingly relies on large-scale models that map language instructions to actions (

arXiv:2605.22878v1 Announce Type: new Abstract: The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmen

arXiv:2605.22711v1 Announce Type: new Abstract: Markov Decision Processes (MDPs) often exhibit significant redundancy due to symmetries and shared structure across state-goal pairs in real-world Goal-

arXiv:2605.21516v1 Announce Type: new Abstract: Harness engineering has emerged as an important inference-time technique for large language model (LLM) agents, aiming to improve long-term performance

arXiv:2605.22205v1 Announce Type: cross Abstract: Large language models increasingly require specialization across diverse domains, yet existing approaches struggle to balance multi-domain capacities

arXiv:2605.21680v1 Announce Type: new Abstract: While autonomous multi-robots can achieve safe and coordinated navigation, they often struggle to adapt to unforeseen conditions and to capture operator

arXiv:2605.22036v1 Announce Type: new Abstract: Despite significant progress in Vision-Language Navigation (VLN), existing approaches still rely on dense RGB videos that produce excessive patch tokens

Disaggregated infrastructure is displacing the all-in-one data center stack — and the economics of AI are making that reality impossible to ignore. The vast majority of enterprise data still resides o

arXiv:2605.12321v2 Announce Type: replace Abstract: Large language models (LLMs) show strong potential for Intelligent Transportation Systems (ITS), particularly in tasks requiring situational reasoni

arXiv:2605.20623v1 Announce Type: cross Abstract: We establish explicit lower bounds for advection-diffusion equations in three settings: a polynomial ot H^{-1} bound for inviscid shears with uin L^in

arXiv:2506.19500v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly act as function-call agents that invoke external tools to tackle tasks beyond their static knowledge