Search: “reasoning”

arXiv:2609.05882v1 Announce Type: cross Abstract: Multi-turn interaction creates a feedback process in which an LLM's previous responses become context for later behavior. Prior work shows substantial

applicationsarxiv-cs-ai

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When Agent Governance Helps

DGX agent

arXiv:2609.05531v1 Announce Type: cross Abstract: No specification says how a governed autotelic AI agent organization, where agents pursue self-generated goals inside guardrails, should be designed a

model-releasesarxiv-cs-ai

10 Sept 2026

When Auditors Fabricate: Batch-Size Degradation and Confident Hallucination in LLM Detection of Planted Document Contamination

model-releasesarxiv-cs-cl

arXiv:2609.09696v1 Announce Type: new Abstract: Large language models are increasingly proposed as automated auditors of document quality, yet their reliability as detectors of planted errors is poorl

Which Medical Questions Deserve Rationales? Perturbation-Sensitive Selection for Robust QA

arXiv:2609.09684v1 Announce Type: new Abstract: Medical question-answering datasets often contain answer labels, whereas high-quality rationales remain scarce, noisy, or costly to validate. This chang

researcharxiv-cs-cl

Why Do LLM Agents Fail in Exploring New Environments? A World-Modeling Perspective

arXiv:2510.15047v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) as agents often fail to improve in new environments. We identify and characterize a failure mode we call explorat

safetyarxiv-cs-cl

3DWay: Generalizing Robot Manipulation via 3D Consistent Waypoints

model-releasesarxiv-cs-ro

arXiv:2609.08224v1 Announce Type: new Abstract: Intermediate representations are key to bridging the modality gap between generalizable manipulation policies and large-scale pretrained vision-language

AhaBench: Do Agents Learn from Prior Experience? A Benchmark for Long-Horizon Continual Learning

arXiv:2609.05435v1 Announce Type: new Abstract: Modern language agents are expected to operate over long horizons: they ask follow-up questions, reuse worked examples, handle tool feedback, and adapt

AV-SafetyBench: A Safety Benchmark for Text-to-Audio-Video Generation

arXiv:2609.06991v1 Announce Type: new Abstract: Recent text-to-audio-video (T2AV) models jointly generate video, speech, sound effects, and ambience from a single text prompt. This capability poses ne

Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generation

arXiv:2609.07720v1 Announce Type: new Abstract: Long-form narrative-to-film generation requires shot-level controllability and cross-clip consistency in both visual identity and character behavior-req

agentsarxiv-cs-cv

Bigger Text Encoders Can Hurt CLIP Zero-Shot Performance

arXiv:2609.05730v1 Announce Type: new Abstract: Contrastive Language-Image Pretraining (CLIP) is a building block of many machine learning applications. Scaling laws have guided resource allocation fo

CausalBN-Bench: A Comprehensive Benchmark for Causal Learning Capability of LLMs

arXiv:2404.06349v3 Announce Type: replace Abstract: The ability to understand causality significantly impacts the competence of large language models (LLMs) in output explanation and counterfactual re

CGSM: Concept-Guided Segmentation Model for Precise Pulmonary Lesion Delineation

arXiv:2609.07004v1 Announce Type: new Abstract: Accurate segmentation of pulmonary lesions is essential for effective clinical diagnosis and treatment strategies. Existing segmentation approaches ofte

Charts Are Beyond Pixels: Probing for Layer-Wise Chart Understanding and Editing

arXiv:2609.08657v1 Announce Type: new Abstract: Charts are structured visual compositions whose elements have distinct functional roles, semantic correspondences, and visibility relations. This struct

Discovering Natural Transformation Vulnerabilities in Black-Box Vision Models

arXiv:2609.07110v1 Announce Type: new Abstract: Natural adversarial examples (NAEs) reveal that vision models can fail under realistic semantic changes beyond norm-bounded perturbations. However, gene

Evaluation of Contextual Understanding in Large Language Models

arXiv:2609.09004v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate impressive performance across diverse NLP tasks, yet their ability to exhibit genuine contextual understandin

Federated Binary Gating with Server-Side Vision-Language Inference for Surveillance Anomaly Classification

arXiv:2609.07403v1 Announce Type: new Abstract: Privacy-sensitive surveillance systems could benefit from large vision-language models (VLMs), but such models typically require centralized access to r

FIRE3D: Feed-forward Interactive 3D Scene Reconstruction Within A Minute

arXiv:2609.08848v1 Announce Type: new Abstract: We present FIRE3D, a unified framework that takes a single RGB image or casual RGB video and transforms it into simulation-ready 3D scene assets for gam

FRAME: Factored Retrieval via Attribute Readouts for Object-Centric Scene Memory

arXiv:2609.08886v1 Announce Type: new Abstract: Language-guided robots need persistent scene memories to follow instructions, revisit objects, and resolve references to objects encountered over time.

From Coordinates to Candidate Regions: Temporal Change Localization via Region Selection in Remote Sensing Multimodal LLMs

arXiv:2609.08391v1 Announce Type: new Abstract: Remote sensing multimodal large language models (RS-MLLMs) have advanced scene understanding and visual question answering over satellite imagery, yet l

GradeTrap: Authority Cues in Images Shift VLM Judgments Despite Explicit Instructions to Ignore Them

arXiv:2609.06058v1 Announce Type: new Abstract: As vision-language models (VLMs) become increasingly capable and are deployed in consequential real-world settings, they must evaluate evidence independ

Human-Aware Target Tracking and Navigation: Fusing Kinematic State Estimation with Structural Map Constraints

arXiv:2609.07091v1 Announce Type: new Abstract: Autonomous mobile robots performing person-following tasks often suffer from temporary occlusions and sensor track loss in dynamic environments. This re

agentsarxiv-cs-ro

Interpretable and Fair Generalized Additive Neural Networks via Multi-objective Learning

arXiv:2609.05946v1 Announce Type: new Abstract: Interpretability and fairness are two of the most emphasized dimensions in trustworthy artificial intelligence (AI). Various explainable AI methods have

safetyarxiv-cs-lg

Is Single-View Mesh Reconstruction Ready for Robotics?

arXiv:2505.17966v3 Announce Type: replace-cross Abstract: This paper evaluates single-view mesh reconstruction models for their potential in enabling instant digital twin creation for real-time planni

Knowledge-Guided Vision-Language Inference for Image-Based Urban Flood Depth Estimation

arXiv:2509.04772v2 Announce Type: replace Abstract: Timely floodwater depth estimates support road accessibility assessment and emergency response during urban flooding. Supervised vision methods ofte

NEST: Narrative Event Structures in Time for Long Video Understanding

arXiv:2606.19706v2 Announce Type: replace Abstract: Recent progress in vision-language models has enabled processing of increasingly long video sequences, but handling extended token streams does not

Nice paper to improve inference efficiency. It's been a while we haven't seen good work on efficiency. Here is why it matters: A long-runnin…

Nice paper to improve inference efficiency. It's been a while we haven't seen good work on efficiency. Here is why it matters: A long-running agent's workspace outgrows its context window long before

model-releasesdair-ai--x

Observing Health Outcomes Using Remote Sensing Imagery and Geo-Context Guided Visual Transformer

arXiv:2602.00110v2 Announce Type: replace Abstract: Visual transformers have driven major progress in remote sensing image analysis, particularly in object detection and segmentation. Recent vision-la

safetyarxiv-cs-cv

Hardware

OCTN: Neural OCT Representations for Robot-Guided Precision Intervention

arXiv:2609.06810v1 Announce Type: new Abstract: Optical coherence tomography (OCT) offers compact, contactless, micron-scale imaging suitable for intraoperative guidance, but native OCT volumes are di

hardwarearxiv-cs-ro

PhysFlow: Physics-Aware Optical Flow for Motion Controllable Video Generation

arXiv:2609.08215v1 Announce Type: new Abstract: Video generation models have recently attracted substantial attention for their ability to generate visually compelling videos, yet ensuring physically

Poisson Image Denoising Using Minimax Concave and Reweighted ell_1 Penalties: Nonblind and Blind Approaches

arXiv:2609.07916v1 Announce Type: new Abstract: Images are important tools in various sciences. Despite the development of photo-taking tools, creating clear and image without noise remains challengin

agentsarxiv-cs-cv

Tutorials

Positive Sample Propagation along the Audio-Visual Event Line

arXiv:2104.00239v3 Announce Type: replace Abstract: Visual and audio signals often coexist in natural environments, forming audio-visual events (AVEs). Given a video, we aim to localize video segments

tutorialsarxiv-cs-cv

ProtoRAG: Prototype-Based Retrieval Augmentation for Few-Shot Fine-Grained Remote Sensing Object Detection

arXiv:2609.05953v1 Announce Type: new Abstract: Few-shot fine-grained object detection (FGOD) in remote sensing imagery is challenging because limited annotations must support both object localization

Qwen3.8-27B-Uncensored-Genesis-V1-GGUF

model-releasesr-localllama

Model available here: Qwen3.8-27B-Uncensored-Genesis-V1-MTP-GGUF This model is a practical realisation of things described in this paper, but adapted by me for machine learning: https://arxiv.org/pdf/

RAH-VLA: Resolution-Adaptive Hierarchical Vision-Language Alignment for Multimodal Remote Sensing Understanding

arXiv:2512.23243v3 Announce Type: replace Abstract: Multimodal vision-language modeling has emerged as a promising paradigm for remote sensing (RS) image understanding. However, existing methods are l

safetyarxiv-cs-cv

ReactVAU: A Slow-Fast Decoupled Framework for Streaming Video Anomaly Understanding

arXiv:2609.07941v1 Announce Type: new Abstract: In this paper, we propose ReactVAU, a Slow-Fast Decoupled Framework for real-time streaming Video Anomaly Understanding (VAU). Existing VAU methods rely

ReLI: Cross-Lingual Language-to-Action Grounding for Human-Robot Interaction

arXiv:2505.01862v4 Announce Type: replace Abstract: Adapting autonomous agents for real-world industrial, domestic, and other daily tasks is currently gaining momentum. However, in global or cross-lin

agentsarxiv-cs-ro

Report of the 8th LSVOS Challenge: Complex and Multimodal Video Object Segmentation

arXiv:2609.06078v1 Announce Type: new Abstract: This report summarizes the 8th Large-scale Video Object Segmentation (LSVOS) Challenge, held in conjunction with ECCV 2026. The challenge evaluates vide

agentsarxiv-cs-cv

Selective Knowledge Control for Continual GUI Agent Learning over Application Streams

arXiv:2609.06530v1 Announce Type: new Abstract: Continual learning is a crucial capability for Graphical User Interface (GUI) agents to adapt to evolving applications while retaining knowledge acquire

Steering Under Compression: Dose-Response, Capability Cost, and Failure Asymmetry in Quantized LLMs

arXiv:2609.06473v1 Announce Type: new Abstract: Inference-time activation steering enables behavioral control of large language models without parameter modification, while post-training quantization

Time-Aware Assistive Navigation

arXiv:2609.05596v1 Announce Type: new Abstract: Can interactive vision-and-language agents learn not just what to say but also extbf{extit{when}} to say it? Current language models rarely plan over wh

VERPO: Verified Evidence Regularized Policy Optimization

arXiv:2609.06100v1 Announce Type: new Abstract: Verifiable outcome rewards guide language-model post-training, but sequence-level advantages do not identify which token-level decisions should be prese

VEX-Bench: Benchmarking LLM Agents for Assessing Exploitability of Software Supply Chain Vulnerabilities

arXiv:2609.08040v1 Announce Type: cross Abstract: The software supply chain has become an increasingly exposed attack surface because of its reliance on intricate yet fragile dependencies. Existing de

Vision-Encoder Behavioral Fingerprints of Image-to-Image Generative Models: A Training-Paradigm-Driven Taxonomy of Six Commercial APIs

arXiv:2606.14787v2 Announce Type: replace Abstract: We study six production image-to-image AI systems (gpt-image-1, Gemini 2.5 Flash Image, Flux Kontext, SDXL img2img, SD3 img2img, and Qwen Image Edit

Weakly supervised neural network: segmentation of complex structures in X-ray microCT

arXiv:2609.07313v1 Announce Type: cross Abstract: Segmentation of complex structures in X-ray tomographic data is a fundamental task in biomedical research, but it often requires large amounts of prec

We're introducing Q2D-Web (Query2Doc-Web), a benchmark and public leaderboard for evaluating retrieval in agentic RAG systems. Q2D-Web tests…

model-releasesperplexity--x

We're introducing Q2D-Web (Query2Doc-Web), a benchmark and public leaderboard for evaluating retrieval in agentic RAG systems. Q2D-Web tests how embedding models perform on large-scale web search usin

Astra feels like a downgrade for writers, editors, and documentation work

What is Astra actually supposed to be better at, Because if the answer is “everything,” then I genuinely do not understand what kind of testing was done for writing-heavy use cases. My biggest issue i

model-releasesr-chatgpt

8 Sept 2026

On the Value of Human Ideas: What data poisoning research reveals about 'autonomous' AI breakthroughs

model-releasesr-localllama

I was reading up on the recent controversy around Tristan Buckmaster, Levent Alpöge, OpenAI, and the Navier–Stokes result, and it got me thinking about something broader than this particular dispute.

8 Sept 2026

We have just raised 3B€ to accelerate our R&D. We are scaling up our training and inference compute to build future generations of our model…