Search: “agents”

Anticipating the Consequences of Curriculum Decisions with Large Language Models

model-releasesarxiv-cs-lg

arXiv:2610.04604v1 Announce Type: new Abstract: Automatic curriculum learning can improve the effectiveness of reinforcement learning by selecting the training experiences presented to the agent over

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ArticuTable: Generating Instance-Level Interactive Rigid-Articulated 3D Tabletop Scenes from a Single Image

DGX agent

arXiv:2610.05249v1 Announce Type: new Abstract: Embodied agents benefit from 3D environments that combine visual fidelity to real-world observations with physical interactivity. Existing single-image

applicationsarxiv-cs-cv

6 Oct 2026

Controllable Road Marking Generation

model-releasesarxiv-cs-cv

arXiv:2610.05771v1 Announce Type: new Abstract: Lane and road markings provide critical guidance for vehicle navigation and multi-agent coordination, yet authoring them at scale remains a manual workf

EvoState: Closed-Loop Visual State Management for Long-Form Video Generation

model-releasesarxiv-cs-cv

arXiv:2606.16184v2 Announce Type: replace Abstract: Multi-shot long-form video generation remains challenging due to identity drift and compounding inconsistencies across shots. Existing methods encod

Recurrent Latent Visual Search for GUI Grounding

arXiv:2610.05185v1 Announce Type: new Abstract: GUI grounding is a critical capability for GUI agents powered by vision-language models, helping them execute user instructions by locating the correspo

safetyarxiv-cs-cv

Hardware

RESOLVE: Language-Agnostic Validation of GPU Kernels Through Testing, Reduction, and Proof

arXiv:2610.05683v1 Announce Type: cross Abstract: AI systems can now write and optimize production GPU kernels, but validating them remains an important challenge. Evaluating the kernel on a few rando

hardwarearxiv-cs-lg

Separating Decision Time from Decision Quality in the Real-Time Gap of Distilled Deciders: Evidence from a Game and a Conveyor Simulator

arXiv:2610.04810v1 Announce Type: new Abstract: Real-time agents are often evaluated with the world paused, or with decision time rounded to whole ticks (tick conversion). Tick conversion predicts alm

Visual Grounding Safety in Vision-Language Models

arXiv:2610.05637v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly trained to generate structured outputs like points and bounding boxes that downstream interfaces, agent

safetyarxiv-cs-cv

When Is Enough Enough in Self-Evolving LLM Systems?

model-releasesarxiv-cs-lg

arXiv:2610.04756v1 Announce Type: cross Abstract: Self-evolving large language model (LLM) systems repeatedly propose, evaluate, and incorporate updates to prompts, skills, or other persistent artifac

Hardware

Batched Speech Decisions Without Decoding: Single-Token Supervision Lets a Frozen LLM Hear Beyond the Transcript

arXiv:2610.02638v1 Announce Type: new Abstract: Full-duplex voice agents make many small, closed decisions, which current systems answer by slow autoregressive decoding. We propose DuplexJev, which fe

hardwarearxiv-cs-ai

Beyond Single Videos: Benchmarking and Active Evidence Seeking for E-Commerce Cross-Video Reasoning

arXiv:2610.03099v1 Announce Type: cross Abstract: E-commerce videos are information-dense and frequently compared by consumers evaluating products and merchants assessing marketing strategies. However

FASTDIAR: Frame-level speaker encoder for Streaming Diarization

arXiv:2610.02941v1 Announce Type: cross Abstract: Real-time conversational agents require speaker diarization that streams and runs on a CPU. Most systems apply an utterance-level speaker encoder to s

PowerBench: Measuring Language Model Bias in Power-shifting Requests

arXiv:2610.02303v1 Announce Type: new Abstract: Language models increasingly assist people with power-related requests, so systematic differences in whom they help could shift the distribution of powe

Reliability Stress Tests and Decision-Time Routing for Chest X-ray Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2610.02270v1 Announce Type: cross Abstract: Medical vision-language model (VLM) evaluation is sensitive to workflow design, prompting strategy, and benchmark construction, yet most studies treat

Scaling Trajectories for Complex Tasks through Recursive Self-Rewrite

arXiv:2610.02826v1 Announce Type: new Abstract: Successful trajectories on difficult tasks provide valuable supervision for model improvement, but specialized harnesses introduce interventions that ma

When a Correct Reward Is Not Enough: Diagnosing and Guiding PPO in an Analytically Solved Broker-Trader Game

arXiv:2610.03598v1 Announce Type: cross Abstract: Reinforcement learning (RL) is increasingly used for financial optimal-control problems when complex dynamics make analytical strategies difficult to

Causal Memory Policy: Making Memory Utility Identifiable by Intervening on Retrieval

arXiv:2610.02070v1 Announce Type: new Abstract: Memory-augmented large language models must decide which memories to retain, and recent systems do so by estimating each memory's effect on task perform

DuoMind: Enabling Distributed Multi-Robot Coordination with Semantic Communication

arXiv:2610.02161v1 Announce Type: cross Abstract: Vision-language models (VLMs) and vision-language-action models (VLAs) have recently driven rapid progress in general-purpose robots, yet most progres

EfficientRollout: System-Aware Self-Speculative Decoding for RL Rollouts

arXiv:2606.18967v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a representative post-training paradigm for large language models (LLMs), enabling strong reasoning and agent

EviGraph: Proof-Carrying Selective Recommendation over Temporal Public-Service Knowledge Graphs

arXiv:2610.00212v1 Announce Type: new Abstract: Public-service recommendations require evidence that matches the requested service, scope, and date. Yet treating every missing detail as decisive can w

FocusGraph: Graph-Structured Frame Selection for Embodied Long Video Question Answering

arXiv:2603.04349v2 Announce Type: replace Abstract: Understanding long videos is crucial for embodied intelligent agents, as their performance depends on effectively accumulating and using long-horizo

researcharxiv-cs-cv

JEPA-Bisim: Learning Robust Visual Representations for Planning with Joint-Embedding Predictive World Models

arXiv:2602.18639v2 Announce Type: replace Abstract: World models learned from high-dimensional visual observations allow agents to make decisions and plan directly in latent space, avoiding pixel-leve

JEPA-TTT: Persistent Test-Time Training of Latent World Models for Planning under Dynamics Shifts

arXiv:2610.00722v1 Announce Type: new Abstract: World models enable agents to plan by predicting future states of the environment, but their predictions can become unreliable when test-time dynamics d

LabBook: Harnessing Experimental History for Efficient LLM-Driven Discovery

arXiv:2610.00675v1 Announce Type: cross Abstract: Evolutionary approaches to LLM-driven discovery often generate new programs from a small set of selected ancestors. This keeps contexts manageable but

Learning Commute-Time-Preserving World Models for Planning

arXiv:2610.01373v1 Announce Type: new Abstract: World models allow agents to plan in latent space by choosing a sequence of actions that most reduces the distance to a given goal state. Thus, planning

Modeling The Object Representations Underlying Human Physical Reasoning

arXiv:2602.12486v2 Announce Type: replace-cross Abstract: Humans appear to represent objects when reasoning about physics with coarse, volumetric 'bodies' that smooth concavities, trading fine visual

Moloch's Bargain: Emergent Misalignment When LLMs Compete for Audiences

arXiv:2510.06105v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly shaping how information is created and disseminated, from companies using them to craft persuasive adv

Network World Models as Environments for Algorithm Design on Complex Systems

arXiv:2610.01048v1 Announce Type: new Abstract: World models, which simulate an environment and predict how it changes under actions, are increasingly used in real-world applications such as robotics.

Science or Slop?: Benchmarking and Mitigating Scientific Slop in AI-Generated Papers

arXiv:2610.00531v1 Announce Type: new Abstract: AI-generated content, often called AI slop, is increasingly common everywhere, particularly in academia. Slop in AI-generated scientific papers, however

The Innocent Courier: Covert Exfiltration Through Legitimate LLM Web Fetching

model-releasesarxiv-cs-lg

arXiv:2610.01768v1 Announce Type: cross Abstract: With the increasing capabilities of Large-Language-Models (LLMs) and LLM-based agents, users are increasingly using them to solve everyday problems, s

Hardware

Training-Free Diffusion Planning with Analytical Local Scores

arXiv:2610.01959v1 Announce Type: cross Abstract: Path finding and multi-robot motion planning require trajectories that are smooth, goal-directed, and collision-free in environments with complex geom

hardwarearxiv-cs-lg

World Motion Models: Flexible Sequence Modeling of SE(3) Trajectories

arXiv:2610.01742v1 Announce Type: cross Abstract: Equipping artificial agents with spatial intelligence requires a comprehensive generative prior over the dynamic 3D world. We propose World Motion Mod

safetyarxiv-cs-cv

AVERT-VLN: Abstention-aware Visual Error Recovery and Training for Vision-and-Language Navigation

arXiv:2609.39579v1 Announce Type: new Abstract: Deploying vision-and-language navigation (VLN) agents in unseen environments remains challenging because unfamiliar layouts and visual conditions can ca

Behavior-Grounded Semantic Enrichment for Financial Fraud Modeling and Reasoning

arXiv:2609.34211v2 Announce Type: replace Abstract: In financial fraud detection, rich semantic context can provide important evidence for transaction behavior modeling and fraud reasoning. However, p

DashVMC: Real-Time Discrete World Model Control in Geometry Dash

arXiv:2609.40003v1 Announce Type: new Abstract: World-model agents are usually evaluated in simulators that can wait for the policy; live games impose the opposite constraint, requiring capture, predi

Fyan: A Human--AI Harness with Semantic Auditing for Document-Level Formalization

arXiv:2609.39228v1 Announce Type: new Abstract: We present FYAN, a human--AI harness for document-level mathematical formalization. Rather than treating theorems in isolation, FYAN coordinates an end-

Hierarchical Reasoning Model

arXiv:2506.21734v4 Announce Type: replace Abstract: Reasoning, the process of devising and executing complex goal-oriented action sequences, remains a critical challenge in AI. Current large language

LatentHarness: Learning Latent Actions for Memory and Reasoning via Counterfactual Policy Distillation

arXiv:2609.39740v1 Announce Type: new Abstract: Long-context reasoning faces two complementary bottlenecks: retaining evidence across long inputs and sustaining computation across many reasoning steps

safetyarxiv-cs-cl

Local Ai

Learning to Plan from Random Exploration

arXiv:2609.38383v1 Announce Type: new Abstract: Random exploration reveals how an environment can be traversed before a goal is specified. Can this experience support long-range planning without polic

local-aiarxiv-cs-lg

Reinforcement Learning with Complex (valued) Memories

arXiv:2609.38598v1 Announce Type: new Abstract: Partially observable environments pose a fundamental challenge in deep reinforcement learning, requiring agents to compress temporal information from ob

Right Answers, Costly Models: The Efficiency Gap in LLM-based Optimization Modeling

arXiv:2609.38884v1 Announce Type: cross Abstract: Optimization modeling formulates real-world decision problems as mathematical programs that solvers can use to find optimal decisions. Large language

Searching for BSM Experimental Signatures with Large Lagrangian Models

arXiv:2609.38309v1 Announce Type: cross Abstract: The search for physics Beyond the Standard Model (BSM) is generally limited not by the supply of theory descriptions but by the lack of discriminating

TERRA: Terrain-Aware Reconstruction, Retargeting and Control for Musculoskeletal Locomotion

arXiv:2609.38653v1 Announce Type: cross Abstract: Recent advances in musculoskeletal modeling and reinforcement learning have enabled muscle-actuated agents to reproduce increasingly complex human mot

Local Ai

Trust the Critic More

arXiv:2609.39247v1 Announce Type: cross Abstract: Standard language model RL algorithms credit every token of a long rollout with the same advantage determined by the terminal reward. Actor-critic met

local-aiarxiv-cs-ai

Trustworthy Runtime Error Healing in Real-World Repositories: A Benchmark and Guardrail

arXiv:2609.39086v1 Announce Type: cross Abstract: Runtime error healing lets a crashed program continue by generating code that repairs its live runtime state. Recent work shows that LLMs can generate

Yggdrasil: a Layer-First 3D Scene Graph for Real-Time Querying

model-releasesarxiv-cs-ro

arXiv:2609.38640v1 Announce Type: new Abstract: Robotic agents use 3D scene graphs (3DSG) to perform tasks ranging from scene understanding to scene interaction. Although an extensive body of work add

Local Ai

ATTUNER: Recomputation-Free KV Cache Reuse via Query-Side Adaptation

arXiv:2609.36722v1 Announce Type: new Abstract: Large language model (LLM) agents repeatedly load reusable content, such as skills, documents, and memory entries, into the current context. Re-encoding

local-aiarxiv-cs-cl

30 Sept 2026

Can AI Scientists Change Their Minds? Prior-Evidence Conflict in Synthetic Universes

arXiv:2609.36726v1 Announce Type: new Abstract: Can a scientific agent distinguish a law it inferred from evidence from one it merely recognizes? We introduce Synthetic Universes, a controlled benchma