Search: “models”

Temporal Learning for End-Effector Position Estimation under Aerodynamic Disturbances in Aerial Continuum Manipulation

arXiv:2609.28716v1 Announce Type: cross Abstract: This paper investigates temporal neural networks for mbox{end-effector} position mbox{estimation} of an aerial continuum manipulator (ACM) operating u

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Safety

The Impossible Trinity of Time-Series Validation: A Conservation Law among Training Sufficiency, Test Coverage, and Temporal Causality

DGX agent

arXiv:2609.29530v1 Announce Type: new Abstract: Validating a model on a time series asks for three things at once: each training run should use most of the sample (sufficiency), the test sets should t

safetyarxiv-cs-lg

25 Sept 2026

There is an extensive and ongoing review related to our agents’ use of internet access during training and evaluation. We’ve been publishing…

There is an extensive and ongoing review related to our agents’ use of internet access during training and evaluation. We’ve been publishing summaries at the link below and will continue to. We have n

agentssam-altman--x

Training-free Behavior Cloning

arXiv:2609.30134v1 Announce Type: new Abstract: Neural behavior cloning compresses demonstrations into large models, making individual actions difficult to trace and policy updates costly. Retrieval p

safetyarxiv-cs-ro

UNWIND: Any-Length Facial Video for Stress Detection without Temporal Windowing

arXiv:2609.29553v1 Announce Type: cross Abstract: Automatic stress recognition from facial video provides a non-contact approach for affective monitoring. However, most existing video-based methods di

When Can Agents Forget Their Reasoning? ICLR for Long-Horizon Agent Context Compression

arXiv:2609.29875v1 Announce Type: new Abstract: Long horizon language model agents continually accumulate reasoning history, increasing context length and inference cost even after earlier decisions h

When Does Unsupervised Learning Succeed or Fail? A PoS Perspective on Reconstruction-Based Anomaly Detection

arXiv:2609.28832v1 Announce Type: new Abstract: Reconstruction-based unsupervised learning can fail in two opposing ways: a model may reconstruct anomalies too accurately or discard valid nominal vari

When Should Forecasting Agents Reason? Behavioral Stress Tests for Reliability Routing

arXiv:2609.28475v1 Announce Type: new Abstract: Forecasting agents increasingly combine language-model reasoning, retrieval, ensembling, and calibration, but it remains unclear when each behavior shou

World Action Agent: Harnessing VLMs for Robot Manipulation via World Action Rehearsal

arXiv:2609.29964v1 Announce Type: cross Abstract: General-purpose vision-language models (VLMs) bring broad knowledge and spatial reasoning to robot manipulation, yet existing systems either use them

Consequential Behaviour and Representational Fairness in the Validation of Synthetic Research

arXiv:2609.27690v1 Announce Type: new Abstract: Researchers in industry and academia use synthetic survey respondents powered by large language models as substitutes for human samples. These synthetic

safetyarxiv-cs-cl

Contrastive Learning for Authorship Verification

arXiv:2609.28471v1 Announce Type: new Abstract: Our results show that contrastive learning outperforms a classification-based approach to authorship verification under the tested settings. We identify

Applications

ContraVis: Evidence-Grounded Visual Analytics for Contradiction Review in Legal Contracts

arXiv:2609.27014v1 Announce Type: cross Abstract: Legal contracts are structurally complex documents in which contradictions may emerge across distant and interconnected provisions. Although large lan

applicationsarxiv-cs-cl

DAVIO: Dense Monocular-Inertial SLAM with Feed-Forward Initialization and Pose-Conditioned Mapping

arXiv:2609.27702v1 Announce Type: cross Abstract: A camera and an IMU are the minimal sensor setup for metric localization and dense mapping, yet classical visual--inertial filters must wait for paral

local-aiarxiv-cs-cv

Do We Need Complex Topology Control? Distinct-Peer Random Routing Improves Cost-Efficiency in Sparse Multi-Agent Debate

arXiv:2609.27150v1 Announce Type: new Abstract: Multi-agent debate (MAD) has emerged as a promising paradigm for improving the reasoning accuracy of large language models (LLMs) through iterative peer

Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev use cases I have found so far. Jev is a nat…

Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev use cases I have found so far. Jev is a natural fit as a Judge, but it doesn't mean you use it everywhe

agentsdair-ai--x

Fine-Tune, Then Rectify

arXiv:2511.19486v3 Announce Type: replace-cross Abstract: Driven by recent advances in artificial intelligence, a growing literature has demonstrated the potential of using large language models (LLMs

Finite-Sample Probabilistic Safety Certification for AI-Based Grid-Edge Coordination

arXiv:2609.28182v1 Announce Type: new Abstract: Coordinating large population of flexible grid-edge devices can alleviate the need for time-consuming and capital-intensive network upgrades, and AI-bas

Fusion-Aware Direct 3D Gaussian Generation with Structured Patch Latent Flows

arXiv:2609.27779v1 Announce Type: new Abstract: Class-guided 3D object generation is important for intelligent content creation, virtual environments, and digital asset design. Although 3D Gaussian Sp

local-aiarxiv-cs-cv

GLoTouch: Global-to-Local Haptic Perception Using a Parallel Gripper for Object Search, Recognition, and Grasping Without External Vision

arXiv:2609.27695v1 Announce Type: new Abstract: Perceiving objects in the environment is a fundamental capability of autonomous robots. In dark or low-light environments, external cameras often fail t

local-aiarxiv-cs-ro

Hard Negatives Reveal What Easy Negatives Hide: Cross-Lingual Harmfulness Representations Degrade with Resource Tier Under Hard Negatives

arXiv:2609.27758v1 Announce Type: cross Abstract: Safety alignment in large language models is trained primarily in English, and recent work reports that the underlying harmfulness representation surv

HiRE: Hindsight Reward Editing for Policy Finetuning

arXiv:2609.27068v1 Announce Type: new Abstract: Pre-trained robot policies always require finetuning to adapt to specific environments. Reinforcement Learning (RL) offers high performance potential be

safetyarxiv-cs-ro

I am looking to hire PhD students, post-docs, and ML researchers in our Paris office interested in collaborating on fundamental research in …

I am looking to hire PhD students, post-docs, and ML researchers in our Paris office interested in collaborating on fundamental research in AI model safety, not safety rules, not AI policy, not post h

safetyyann-lecun--x

I built a presentation generator that works with Ollama — would love some feedback

Hey r/Ollama, I've been working on Presentation Forge, an open-source presentation/report generator that supports Ollama for local inference. I originally made it because I'm a university student and

local-air-ollama

Impressive paper from Salesforce. It discusses the importance of good verifiers for RL environments. Only 35.8% of the environments in the c…

Impressive paper from Salesforce. It discusses the importance of good verifiers for RL environments. Only 35.8% of the environments in the cleanest public RL collection for terminal agents passed Sale

researchdair-ai--x

Introducing GKE agentic migration for AI-assisted EKS-to-GKE migrations with built-in governance

Enterprises are increasingly standardizing on Google Kubernetes Engine (GKE) to run their most critical and AI-driven workloads. From Cloud Storage FUSE for high-throughput data access to custom compu

local-aigoogle-cloud-ai

Applications

LiAM-SAM: Lifecycle-Aware Memory for Robust SAM2-Based MOT

arXiv:2609.28078v1 Announce Type: new Abstract: Segmentation-based multi-object tracking (MOT) with foundation video models such as SAM2 offers strong localization quality, yet remains fragile in crow

applicationsarxiv-cs-cv

Tutorials

Meet, Compare, or Abstain: LatWeave for Deterministic Multi-Hop Question Answering on Knowledge Lattices

arXiv:2609.27225v1 Announce Type: cross Abstract: Probabilistic question-answering systems -- whether large language models (LLMs) themselves, retrieval-augmented generation (RAG), or trained multi-ho

tutorialsarxiv-cs-ai

ODPure: Backdoor Purification for Object Detection via Ensemble Corruption Consensus

arXiv:2609.28239v1 Announce Type: new Abstract: With the development of applications like autonomous driving, object detection has gained significant attention, while also highlighting critical vulner

agentsarxiv-cs-cv

Passing: An Endless Journey through Reconstructed Spacetime with AI-Generated Sound

arXiv:2609.27489v1 Announce Type: cross Abstract: This paper introduces Passing, an interactive audiovisual installation that generates an endless journey from a single continuous monorail-window reco

PCQC: Privileged Counterfactual Question Credit for Multi-Turn Medical Dialogue

arXiv:2609.27987v1 Announce Type: new Abstract: Large language models (LLMs) have made substantial progress on medical question-answering, yet effective medical dialogue also requires learning to ask

safetyarxiv-cs-lg

Predicting Quantization Price for Selecting PTQ Configurations Before Deployment

arXiv:2609.28270v1 Announce Type: new Abstract: Weight-space post-training quantization (PTQ) must choose finite formats, granularities, quantizer families, transformations, and bits before the comple

ProCredit: From Outcome Rewards to Progress Credit in Agentic Reinforcement Learning

arXiv:2609.27532v1 Announce Type: cross Abstract: Long-horizon agentic tasks require an agent to modify an environment through a sequence of tool calls, with success determined by the final state. The

agentsarxiv-cs-cl

Recursive Uncertainty-Gated Image Registration for Learning-based Algorithms

arXiv:2609.28081v1 Announce Type: cross Abstract: Conventional image registration algorithms are robust to domain shifts and achieve low errors, but they are slow and computationally expensive. Deep-l

researcharxiv-cs-cv

Resource-Adaptive Stochastic Gradient Descent for Online Linear Programming without Re-solving

arXiv:2609.28263v1 Announce Type: new Abstract: The growth of large language model (LLM) inference and search services increases the scale of online linear programming problems, motivating computation

Safe learning-based control via function-based uncertainty quantification

arXiv:2604.01173v2 Announce Type: replace-cross Abstract: Uncertainty quantification is essential when deploying learning-based control methods in safety-critical systems. This is commonly realized by

safetyarxiv-cs-lg

Shared Global KV with Layer-Specific Local History

arXiv:2609.28006v1 Announce Type: new Abstract: Decoder-only Transformer language models cache keys and values (KV) to reuse past computation during generation. Sharing KV across layers saves storage

Shopping by algorithm: How agentic AI deploys human heuristics as a surrogate consumer

arXiv:2609.28372v1 Announce Type: cross Abstract: Consumers increasingly delegate purchasing decisions to Large Language Models (LLMs) acting as surrogate consumers. Using 'Tool-Lab,' an adaptation of

Signal2Symbol: Neuro-Symbolic Temporal Reasoning for Explainable Physiological Time-Series Anomaly Detection

arXiv:2609.26820v1 Announce Type: cross Abstract: Physiological time series such as electrocardiograms (ECG) and electroencephalograms (EEG) exhibit complex temporal structure, substantial acquisition

Tackling fluffy clouds: robust agricultural field boundary delineation from Sentinel-1 and Sentinel-2 satellite image time series

arXiv:2409.13568v3 Announce Type: replace Abstract: Accurate delineation of agricultural field boundaries is essential for effective crop monitoring and resource management. However, competing methodo

researcharxiv-cs-cv

The Like Trap: Multi-Stage Poisoning against Agents in Similarity-based Recommendation Systems

arXiv:2609.27155v1 Announce Type: cross Abstract: With recent advancements in large language models (LLMs) and LLM-based agents, these agents are becoming increasingly autonomous and gaining broader a

Value Mirror Descent for Reinforcement Learning

arXiv:2604.06039v2 Announce Type: replace-cross Abstract: Value iteration-type methods have been extensively studied for computing a nearly optimal value function in reinforcement learning (RL). Under

safetyarxiv-cs-lg

Variational Bayesian Flow Network for Graph Generation

arXiv:2601.22524v2 Announce Type: replace Abstract: Graph generation aims to sample discrete node and edge attributes while satisfying coupled structural constraints. Diffusion models for graphs often

VLMs Can Describe, But Not Measure: Object-Centric Scene Understanding for Robotic Manipulation

arXiv:2609.28184v1 Announce Type: cross Abstract: Robotic operation in previously unseen environments requires both semantic understanding and reliable metric information. While vision--language model

local-aiarxiv-cs-cv

When Learned Context Planning Fails to Beat Strong Retrieval: A Controlled Study of Planning, Routing, and Reranking for Long-Context QA

arXiv:2609.26976v1 Announce Type: new Abstract: Learned context planning selects evidence atoms before an answer model reasons over them. We test whether this learned selection improves long-context m

WTF?! Simulation-Free Reinforcement Learning with Wasserstein-Tilted Flow Maps

arXiv:2609.27033v1 Announce Type: cross Abstract: Reward fine-tuning aims to update a pre-trained flow-based generative model to improve the downstream reward of its generated samples. Existing method

researcharxiv-cs-cv

A Multi-Timestep LSTM Ensemble regressor for Enhanced Short-Term Runoff Prediction

arXiv:2609.26244v1 Announce Type: cross Abstract: Accurately forecasting river runoff is key to managing water resources, controlling floods, and planning agriculture. This study examines the Ajichay

agentsarxiv-cs-lg

23 Sept 2026

AIGC Video Detection based on the fusion of spatial-frequency-optical flow multimodal features

arXiv:2609.26274v1 Announce Type: new Abstract: The rapid evolution of generative AI (e.g., Sora, Hunyuan) makes it essential to develop effective detection strategies that can generalize across ever-

safetyarxiv-cs-cv

23 Sept 2026

ARAFA: An LLM-Generated Arabic Fact-Checking Dataset

arXiv:2609.25833v1 Announce Type: new Abstract: Automatic fact-checking poses a significant challenge in Arabic natural language processing due to the scarcity of datasets and resources. In this manus