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Accurate and Efficient Object Pose Estimation via the Aggregation of Diffusion Features

model-releasesarxiv-cs-cv

arXiv:2403.18791v4 Announce Type: replace Abstract: Estimating the pose of objects from images is a crucial task of 3D scene understanding, and recent approaches have shown promising results on very l

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Agents

Accurate but Not Humble: Evaluating Epistemic Humility in LLM Agents under Knowledge Conflict

DGX agent

arXiv:2610.12360v1 Announce Type: new Abstract: When retrieved evidence contradicts an agent's prior beliefs, does it revise its answer, acknowledge uncertainty, or persist with an incorrect conclusio

agentsarxiv-cs-ai

9 Oct 2026

Acting from Belief, Looking When Needed: A Bayesian Spatial World Model for Navigation under Intermittent Perception

arXiv:2610.11591v1 Announce Type: new Abstract: Robot navigation commonly uses wide-coverage, high-frequency sensing to reduce partial observability; this reliance becomes restrictive when another tas

applicationsarxiv-cs-ro

ActionCodec: What Makes for Good Action Tokenizers

arXiv:2602.15397v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models leveraging the native autoregressive paradigm of Vision-Language Models (VLMs) have demonstrated superior

ActiveMedAgent: Cost-Aware Trajectory Learning for Multimodal Medical Diagnosis

arXiv:2610.11140v1 Announce Type: cross Abstract: Clinical diagnosis is inherently sequential: clinicians escalate from cheap to costly tests only when additional evidence is expected to resolve diagn

ActiveReg: Information-Driven Active Regional Probing for Partial-to-Full Bone Registration

arXiv:2610.11003v1 Announce Type: new Abstract: Accurate bone registration is essential for orthopedic surgical navigation and robotic assistance. In a common workflow, the surgeon needs to identify a

researcharxiv-cs-ro

AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting

arXiv:2610.12240v1 Announce Type: cross Abstract: Time-series foundation models (TSFMs) have achieved strong forecasting performance across domains. However, most adaptation methods remain static. Exi

AdaptEvo: Adaptive Agent Learning with Evolving Supervision

arXiv:2610.11354v1 Announce Type: new Abstract: Rule-governed contextual decision tasks require models to apply specified rules to case-specific context and evidence. Written rules can leave gaps in d

safetyarxiv-cs-cl

Adapting English Quality Classifiers for Multilingual LLM Pretraining Data Selection

arXiv:2610.11585v1 Announce Type: cross Abstract: Recent advances in large language model (LLM) pretraining highlight the role of high-quality training data in improving performance. While model-based

Adaptive Adversarial Augmentation for Controllable Face Synthesis

arXiv:2610.11356v1 Announce Type: new Abstract: Synthetic data provides a scalable alternative to real-world datasets for training face recognition models, particularly under challenging conditions su

applicationsarxiv-cs-cv

Adaptive Multi-Discriminator WGAN Framework for Resource-Constrained Internet of Vehicles Using Reinforcement Learning and Game Theory

arXiv:2610.10926v1 Announce Type: new Abstract: Managing machine learning workloads as a network service introduces a resource-orchestration problem distinct from conventional model training; which no

applicationsarxiv-cs-lg

AdaptLSTM: Efficient Adaptive Online Learning for Cloud Workload Forecasting under Distribution Drift

model-releasesarxiv-cs-lg

arXiv:2610.12265v1 Announce Type: new Abstract: Accurate workload forecasting is critical for elastic resource provisioning in web-scale cloud services, where distribution shifts driven by viral conte

AdaSwitch: An Adaptive Switching Meta-Algorithm for Learning-Augmented Bounded-Influence Problems

arXiv:2509.02302v2 Announce Type: replace Abstract: We study history-dependent online problems with a possibly inaccurate prediction of the future request sequence. Motivated by several real-world app

applicationsarxiv-cs-lg

Addressing Overcommitment in the Reasoning of Gendered Economic Memes under Multimodal Ambiguity

arXiv:2610.11724v1 Announce Type: new Abstract: Multimodal meme understanding is increasingly used to analyze socially sensitive content, yet existing models often exhibit biased behavior when interpr

safetyarxiv-cs-lg

Adversarial Cues in Decision Models Used as Judges: The Role of Request Presentation

arXiv:2610.11436v1 Announce Type: new Abstract: An answer judge instructed to grade the final commitment should reject an explicitly wrong final value even when an earlier value matches the reference.

researcharxiv-cs-cl

AffordDrive3D: Affordance-Aware World-Action Modeling with Spatial Understanding

arXiv:2610.11060v1 Announce Type: cross Abstract: World-action models have recently improved autonomous driving by jointly learning future scene prediction and trajectory generation. Most existing app

Agents

Agent-Controlled Forgetting for Tool-Using Agents: Reversible Context Curation in Practice

arXiv:2610.10590v1 Announce Type: new Abstract: Tool-using agents repeatedly carry observations whose useful content can be much smaller than their original payload. We study agent-controlled forgetti

agentsarxiv-cs-ai

Agent4RE: A Self-Refining Multi-agent Framework for End-to-End Software Requirements Engineering and Benchmarking

arXiv:2610.10628v1 Announce Type: cross Abstract: Existing LLM-based approaches for software Requirements Engineering (RE) typically rely on basic prompting strategies or rudimentary agent collaborati

Agents

AgentEvolver: System-Wide Self-Evolution Through Task Execution

arXiv:2610.11613v1 Announce Type: new Abstract: An agent can complete a task without improving how it works. Turning task experience into reusable capability requires connecting the changed component

agentsarxiv-cs-ai

Agents

AgentFly: Scaling Agentic Reinforcement Learning with Unified Resource System

arXiv:2507.14897v2 Announce Type: replace Abstract: Methods to build LLM agents have evolved from prompt engineering and supervised finetuning to agentic reinforcement learning (agentic RL). However,

agentsarxiv-cs-ai

Tutorials

AgentGarten: Code Worlds for Evolving Agents

arXiv:2610.12374v1 Announce Type: new Abstract: Interactive virtual worlds allow agents to learn through exploration and interaction. What agents can learn is bounded by the environments they practice

tutorialsarxiv-cs-cv

AgentHorizon: Evaluating Agentic Judges for Long-Horizon Computer-Use Tasks

arXiv:2610.11050v1 Announce Type: new Abstract: Computer-use agents are capable of completing complex tasks, increasing the use of automatic judges to determine success, either for training or for eva

Agentic Critical Training

arXiv:2603.08706v2 Announce Type: replace Abstract: Imitation learning (IL) teaches language-model agents to reproduce expert actions but not to distinguish them from plausible mistakes. Self-reflecti

Agentic-TTT: Training test-time policy for test-time training

arXiv:2610.12002v1 Announce Type: cross Abstract: Test-time training (TTT) adapts an LLM's parameters using signals derived from test inputs, and can make striking improvements in pre-specified settin

AgentTime: Can Agents Estimate and Control Their Own Runtime?

arXiv:2610.09944v2 Announce Type: replace Abstract: An essential control of AI agents is their ability to manage runtime. This ability requires a sense of time-awareness, to predict and estimate wall-

AI Appeals Processor: A Deep Learning Approach to Automated Classification of Citizen Appeals in Government Services

arXiv:2604.03672v2 Announce Type: replace-cross Abstract: Government agencies must register, classify and route every citizen appeal within statutory time limits, and much of this work is still done b

applicationsarxiv-cs-ai

AI-Based On-Board Maritime Object Detection for Earth Observation Payload Data Reduction on Versal Embedded Hardware

arXiv:2610.12182v1 Announce Type: cross Abstract: Very-high-resolution Earth-observation satellites acquire more data than they can store and downlink, while in maritime surveillance the vessels cover

AI-Mediated Self: How HCI Defines and Relates to the Self

arXiv:2610.10770v1 Announce Type: cross Abstract: How might AI alter how we understand and experience the self? This scoping review analyzes 102 papers to examine how the self is defined in the field

applicationsarxiv-cs-ai

Industry

AI stocks crumble on report that OpenAI’s annualized revenue is much lower than believed

Technology stocks fell lower today following a report that artificial intelligence giant OpenAI Group PBC’s annualized revenue this year is about $20 billion less than what was previously reported by

industrysiliconangle

Ai2 at COLM 2026: Open research, from models to agents for science

Ai2 joined COLM 2026 to share advances in open language models, training infrastructure, and AI for science, including Olmo Hybrid, Asta, and Bolmo, while connecting with the broader research communit

researchai2

AI4Fire: Evaluating Large Language Models on Wildfire Tasks

arXiv:2610.10946v1 Announce Type: new Abstract: Large language models (LLMs) are entering wildfire management, where overstated evaluations can cost property and lives. How do they perform on wildfire

researcharxiv-cs-cl

Alignment is a human-AI workflow: how Custom Views make agent review possible

Automated evals can score every agent session, but they do not automatically reflect what your team considers a good outcome. That takes human judgment. The post Alignment is a human-AI workflow: how

safetyarize-ai

AliO: Output Alignment Matters in Long-Term Time Series Forecasing

arXiv:2610.11213v1 Announce Type: new Abstract: Long-term Time Series Forecasting (LTSF) tasks, which leverage the current data sequence as input to predict the future sequence, have become increasing

All Verdicts are Not Equal: Rethinking LLM Judge Reliability

arXiv:2610.12083v1 Announce Type: cross Abstract: LLM-as-a-Judge is the standard paradigm for NLP evaluation, yet its systemic reliability remains poorly understood despite being widely treated as a d

Tutorials

Ambient Discrete Diffusion: Using the Wrong Data at the Right Time for Data Efficient Learning

arXiv:2610.12340v1 Announce Type: new Abstract: We introduce RefineMix, a framework for training discrete diffusion models under severe data scarcity, a common constraint in scientific applications. R

tutorialsarxiv-cs-lg

Amortized Off-Policy Evaluation for LLMs

model-releasesarxiv-cs-lg

arXiv:2610.10848v1 Announce Type: new Abstract: Accurate evaluation is central to selecting which LLM to deploy, yet testing a candidate on live traffic exposes real users to an unvetted model. Teams

An Efficient Quantum Circuit for Flow Model Execution Using Quantum Neural Networks

arXiv:2610.11537v1 Announce Type: cross Abstract: Flow models generate trajectories from an initial distribution to a target distribution by solving an ordinary differential equation defined by a velo

researcharxiv-cs-lg

An Explainable Header-Centric Framework for Large-Scale Semantic Table Interpretation and Data Quality Assessment

arXiv:2610.10541v1 Announce Type: new Abstract: Knowledge Graph (KG) quality depends not only on downstream graph validation, but also on the quality of tabular metadata used before integration. In me

Tutorials

An Interpretable Approach to PDE Solution Discovery via Structural Experience Distillation

arXiv:2610.12003v1 Announce Type: new Abstract: PDE solution discovery aims to identify explicit symbolic expressions for unknown physical fields from observations under known physical constraints. Ex

tutorialsarxiv-cs-ai

An Investigation of Model Coherence: Narrow Finetunes Contradict Themselves Under Resampling

arXiv:2610.12129v1 Announce Type: new Abstract: A large body of research measures model coherence based on output variance without adequately considering competing causes. We identify two such causes,

An Investigation of Robustness of LLMs in Mathematical Reasoning: Benchmarking with Mathematically-Equivalent Transformation of Advanced Mathematical Problems

arXiv:2508.08833v4 Announce Type: replace-cross Abstract: Frontier large language models (LLMs) now reach near-ceiling accuracy on standard mathematical-reasoning benchmarks and gold-medal-level perfo

Analyzing and Improving Fine-grained Preference Optimization in Medical LVLMs

arXiv:2606.12590v2 Announce Type: replace-cross Abstract: Preference optimization is increasingly used to post-train medical large vision-language models (LVLMs), yet it operates at a much coarser gra

Anthropic is setting up a 'presidential engagement' program for the 2028 US elections that will offer AI policy education to candidates in both parties (Emily Forlini/Fortune)

Emily Forlini / Fortune: Anthropic is setting up a “presidential engagement” program for the 2028 US elections that will offer AI policy education to candidates in both parties — Anthropic is setting

safetytechmeme

Anthropic’s AI gave Philadelphia police a fake tip about an unsolved homicide

model-releasesthe-verge-ai

An Anthropic AI model provided false information about an unsolved homicide to a Philadelphia Police Department (PPD) tipline, according to a report from 6abc. In a statement released on Friday, the P

Arbiter: Detecting Interference in LLM Agent System Prompts

arXiv:2603.08993v2 Announce Type: replace-cross Abstract: System prompts for LLM-based coding agents are software artifacts that govern agent behavior, yet lack the testing infrastructure applied to c

ARC: A Reasoning Recipe for Robot Foundation Models

arXiv:2610.12386v1 Announce Type: cross Abstract: The prevailing approach to improving robot foundation models (RFMs) relies on larger models, more robot demonstrations, and costly training at scale.

asdex: Automatic Sparse Differentiation in JAX

arXiv:2610.12336v1 Announce Type: cross Abstract: Many tasks in scientific computing and machine learning require the Jacobian or Hessian matrix of a function. Automatic differentiation (AD) computes

researcharxiv-cs-lg

ASPIRE: Saddle-Point Discovery through Set Prediction and Physical Refinement

model-releasesarxiv-cs-lg

arXiv:2610.10969v1 Announce Type: new Abstract: Predicting thermally activated diffusion and defect evolution with event-driven models requires identifying atomic rearrangement mechanisms and their ac