Search: “models”

Certified Interface Aliases: Exact Collisions in Vision-Language Preprocessing, and When They Exist

arXiv:2609.33003v1 Announce Type: new Abstract: Vision-language verifiers and routers must distinguish errors repairable by more reasoning from those caused by visual evidence never reaching the langu

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Clinical Trajectory Alignment for Medical Vision-Language Pre-training

DGX agent

arXiv:2609.34439v1 Announce Type: new Abstract: Medical vision-language pre-training largely follows a visit-level image-report matching paradigm, aligning paired images and reports at individual visi

safetyarxiv-cs-cv

29 Sept 2026

CollisionSplatting: Collision-Aware Motion Planning in 3DGS Scenes with Image-Conditioned Objectives and Adjustable Conservatism

arXiv:2609.35619v1 Announce Type: new Abstract: Incorporating dense visual information into motion planning remains challenging, as geometric planners rely on abstracted scene representations that dis

local-aiarxiv-cs-ro

Contrast Matters: Understanding Robustness of In-Context Fine-Tuning to Target-Context Relatedness

arXiv:2604.01601v2 Announce Type: replace Abstract: In-context fine-tuning (IC-Train), training an LLM with labeled examples in-context, is increasingly used in place of standard fine-tuning for domai

Tutorials

CRF Loss is How Networks Should Learn Boundaries in Weakly Supervised Segmentation

arXiv:2609.34183v1 Announce Type: new Abstract: Weakly Supervised Semantic Segmentation (WSSS) learns pixel-level predictions from image-level tags. Recent work focuses on improving coarse CAMs extrac

tutorialsarxiv-cs-cv

Data Processing for Offline Evaluation in Recommender Systems: a Survey

arXiv:2609.31696v1 Announce Type: cross Abstract: Offline evaluation is the dominant experimental paradigm in recommender systems research, enabling reproducible and cost-effective comparisons on hist

Demonstration-Free Success-Probability Reward Learning for Generalist Robot Policies

arXiv:2609.33653v1 Announce Type: cross Abstract: Reinforcement learning (RL) enables generalist robot policies to improve through trial-and-error interaction, yet its effectiveness is fundamentally c

Diffusion-grounded VideoLLM for Entity-aware temoporal grounding

arXiv:2508.15641v2 Announce Type: replace Abstract: Precise temporal grounding requires distinguishing when a queried event occurs from when its participating entities are merely visible. We propose D

Industry

Dots are here! A new way to use AI that works 24/7 for you; get more of your time and attention back to work at a higher level. https://open…

OpenAI introduced “Dots,” an AI system built to run continuously and free users’ time so they can focus on higher‑level tasks. The announcement was posted on September 29 2026 by CEO Sam Altman via Tw

industrysam-altman--x

Agents

Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems

arXiv:2602.08847v2 Announce Type: replace Abstract: Multi-agent LLM systems enable advanced reasoning and tool use via role specialization, yet reliable reinforcement learning (RL) post-training for s

agentsarxiv-cs-lg

DRIFT: Disentangled Responsive-Invariant Flow Transport for Single-Cell Perturbation Prediction

arXiv:2609.35106v1 Announce Type: new Abstract: Predicting cellular responses to perturbations is a central problem in cellular biology, with broad applications in systems biology and drug discovery.

EfficientAgent: What Makes KV Cache Offloading Work for Concurrent Agents?

arXiv:2609.33762v1 Announce Type: cross Abstract: LLM agents resend their whole conversation on every turn, and most of it was already processed on the previous turn. Serving systems avoid recomputing

Ego-Forge: Text and Geometric-Attention Free Exo-to-Egocentric Video Generation

arXiv:2609.35368v1 Announce Type: new Abstract: Exo-to-egocentric video generation aims to synthesize what a person sees from their own viewpoint given third-person footage and a target head trajector

safetyarxiv-cs-cv

Evasion Attacks on Cost-Utility-Based Adversarial Training for Online AutoML in IoT Networks

arXiv:2609.31981v1 Announce Type: cross Abstract: As Internet of Things (IoT) networks increasingly depend on machine learning for anomaly, malware, intrusion detection, and network monitoring, such s

Agents

ExcavaTwin: Training-Free Geometry-Guided Semantic Elevation Mapping for Autonomous Excavation

arXiv:2609.34719v1 Announce Type: new Abstract: Autonomous excavation requires a spatial representation that jointly captures terrain geometry and task-relevant semantics. Existing excavation mapping

agentsarxiv-cs-ro

Hardware

Fill2SR: Repurposing Inpainting Diffusion Transformers for Real-World Super-Resolution

arXiv:2609.33582v1 Announce Type: new Abstract: Recent real-world image super-resolution (SR) methods often adapt text-to-image (T2I) backbones with ControlNet-style branches or spatial conditioning t

hardwarearxiv-cs-cv

Fiona: Accelerating FHE Inference with Packing-Aware Ternary Weights

arXiv:2609.35352v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) enables neural network inference directly on encrypted inputs, but it remains orders of magnitude slower than plainte

Forecasting Intraday USD/CAD Exchange Rate with News-Derived Monetary-Policy Signals

arXiv:2609.32773v1 Announce Type: cross Abstract: Monetary-policy announcements and central-bank communications play a central role in foreign exchange markets, yet their qualitative, unstructured for

Forlinx 20-TOPS M.2 AI accelerator supports PCIe cascading for local LLM inference

Forlinx Embedded has listed an M.2 AI accelerator card based on Rockchip’s RK1820 and RK1828 processors, providing 20 TOPS of INT8 computing performance and up to 5GB of integrated DRAM. The module us

local-air-localllama

Frequency-Domain AI-Generated Image Detection: Exploring Decoder and Channel Attention for Feature Refinement

arXiv:2609.31723v1 Announce Type: new Abstract: With the rapid progress of AI, the number of AI-generated images has increased significantly in recent years. However, the increasing variety of image g

GenNVS: Geometry-enhanced Novel View Synthesis via Disentangled 3D Prior

arXiv:2609.34579v1 Announce Type: new Abstract: Single-image novel view synthesis remains challenging because the underlying 3D geometry is highly ambiguous. Recent diffusion-based approaches produce

GERIS: A Game-Theoretic Framework for Filtering Instance-Dependent Label Noise in License Plate Data Augmentation

arXiv:2609.31731v1 Announce Type: new Abstract: In this paper, we propose GERIS, a game-theoretic framework for instance selection in the data augmentation phase of license plate recognition systems.

applicationsarxiv-cs-cv

Tools

Good

Good Just arrived at @OpenAI #DevDay, and I’m predicting proactive intelligence will steal the show. We’ve gone from statistics to machine learning to intelligence. Now the next step is AI that doesn’

toolsitamar-friedman--x

GPT-6.1 Sol shows major improvements over GPT-6 Sol in our alignment evaluations, bringing it more in line with GPT-6 Astra. It’s more trans…

GPT-6.1 Sol shows major improvements over GPT-6 Sol in our alignment evaluations, bringing it more in line with GPT-6 Astra. It’s more transparent about its limitations and more reliable at respecting

safetyopenai--x

Groupwise Selective State-Space Filtering for Accurate and Streaming Action Boundary Detection

arXiv:2609.33400v1 Announce Type: new Abstract: Action boundary detection partitions untrimmed video into intervals without assigning action classes. We present a boundary-detection adapter operating

Hard Vision, Easy Vision: What GPT-6 Astra Reveals Across Computer Vision

arXiv:2609.35718v1 Announce Type: new Abstract: Frontier general-purpose systems are rapidly expanding beyond visual understanding into capabilities traditionally handled by dedicated computer-vision

Helical Tendon-Driven Continuum Robot with Programmable Follow-the-Leader Operation

arXiv:2601.13177v2 Announce Type: replace Abstract: Spinal cord stimulation (SCS) is widely used for pain management and has recently shown promise in promoting functional recovery following spinal co

safetyarxiv-cs-ro

How Synthetic Labels Improve Conformal Prediction: A Perspective on Conditional Coverage

arXiv:2609.33482v1 Announce Type: new Abstract: Conformal prediction provides distribution-free finite-sample marginal coverage, but post-hoc calibration data may be too scarce to learn how uncertaint

Improving Video Sparse Attention with Fine-grained Router and Sparse Rebasing

arXiv:2609.32882v1 Announce Type: new Abstract: We present VSA2, a frontier trainable sparse attention for video DiTs. VSA2 includes a variety of new architectural features and training procedures tha

Hardware

In-Flight KV Cache with Clean Anchors for Faster Autoregressive Video Diffusion

arXiv:2609.32540v1 Announce Type: new Abstract: Few-step autoregressive video diffusion generates a long video by splitting the video into temporal chunks and generating chunk-by-chunk, each through a

hardwarearxiv-cs-cv

Information-Theoretic Analysis of Next-Token Prediction under Markovian Data

arXiv:2609.34731v1 Announce Type: cross Abstract: We develop an information-theoretic framework for generalization in next-token prediction under temporally dependent data. We consider independent tra

Last-Iterate Guarantees for Online Reinforcement Learning in Structured Constrained MDPs

arXiv:2609.32933v1 Announce Type: new Abstract: In safety-critical applications, deployment uses a single policy, whose performance and constraint satisfaction should hold directly rather than only fo

Leaky Students: Membership Inference against On-Policy Distillation

arXiv:2609.33136v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student to match a teacher's next-token distributions on student-generated trajectories. However, privileged infor

Learning Domain- and Class-Disentangled Prototypes for Domain-Generalized EEG Emotion Recognition

arXiv:2509.01135v3 Announce Type: replace Abstract: Electroencephalography (EEG)-based emotion recognition plays a critical role in affective Brain-Computer Interfaces (aBCIs), yet its practical deplo

applicationsarxiv-cs-lg

LocalProp: Neuro-Localized Memory-Efficient Backpropagation

arXiv:2609.32517v1 Announce Type: cross Abstract: The current deep learning training paradigm employs end-to-end backpropagation, regardless of the training stage, i.e. pre-training or fine-tuning. Ho

local-aiarxiv-cs-cv

MASCIT: A Mask-Aware State Space Classifier for Naturally Irregular Time Series

arXiv:2609.34409v1 Announce Type: new Abstract: Naturally irregular time series combine asynchronous observations, missing values, unequal lengths, and nonuniform sampling, while dense adapters can di

Agents

Measurement Boundaries in LLM Financial Agent Evaluation: Fixed-Tape Execution and Multi-Defect Auditing

arXiv:2609.32379v1 Announce Type: new Abstract: What controls are needed to interpret execution performance and audit scores in LLM agent evaluations? We study two limits on these interpretations in a

agentsarxiv-cs-lg

MM-ABC: Towards Generalist Mobile Manipulation via Seeing, Coordinating and Imagining

arXiv:2609.35652v1 Announce Type: new Abstract: Mobile manipulation extends robot interaction beyond a fixed kinematic workspace by making the reachable region itself controllable. This flexibility in

applicationsarxiv-cs-ro

Multi-Modal Non-Prehensile Estimation of Physical Parameters via Press-and-Pull Tipping

arXiv:2609.33138v1 Announce Type: new Abstract: Recovering physical properties of unknown objects through non-prehensile interaction is challenging because no single manipulation primitive reveals all

researcharxiv-cs-ro

NutriVision: Ingredient-Conditioned Fusion and Prediction for Single-Image Food Nutrition Estimation

arXiv:2609.33076v1 Announce Type: new Abstract: Nutrition estimation is a fundamental task in consumer diet tracking, clinical dietetics, chronic disease management, sports and hospital nutrition, and

One Sequence, Many Decodings: CAGenMol-2 Recasts Drug Design as Masked Molecular Inference

arXiv:2609.34301v1 Announce Type: new Abstract: Drug design couples property evaluation, conditional generation, structure-based design, and local optimization, yet machine learning systems typically

local-aiarxiv-cs-lg

Optimal transport meets speech: a tutorial review

arXiv:2609.31787v1 Announce Type: cross Abstract: Optimal Transport (OT) provides a principled framework for comparing and transforming probability distributions while preserving geometric structure.

Physics-Informed Neural Networks with Architectural Physics Embedding for Large-Scale Wave Field Reconstruction

arXiv:2603.02231v2 Announce Type: replace Abstract: Large-scale wave field reconstruction requires precise solutions but faces challenges with computational efficiency and accuracy. The physics-based

Plan-to-Synthesis: Cross-City Human Mobility Generation via Semantic Latent Flow Matching

arXiv:2609.32732v1 Announce Type: cross Abstract: Human mobility generation aims to synthesize realistic point-of-interest (POI) visitation trajectories and has become an important tool for travel beh

Predicting the Financial Impact of Supply Chain Risk for Major AI-Related Semiconductor Firms: A Heterogeneous Graph Patch Transformer Approach

arXiv:2609.32741v1 Announce Type: new Abstract: Modern semiconductor production relies on a globally distributed, multi-tier supply chain in which financial stress at one firm spreads with a delay and

applicationsarxiv-cs-lg

Predictive Semantic Safety: From Visual Physical Reasoning to Safety-Critical Control

arXiv:2609.34356v1 Announce Type: cross Abstract: Physical interactions can create future hazards that are not apparent from the robot's current geometric surroundings. We present a framework termed P

Hardware

PrefLUT: Reusable and Refinable Personalized Color Editing from Pairwise Preferences

arXiv:2609.34133v1 Announce Type: new Abstract: Photographic color editing is inherently personal: the same image can appear too warm, too muted, or already satisfactory to different users. Most looku

hardwarearxiv-cs-cv

Pretraining Transformers with Quantized Softmax in Attention

arXiv:2609.33591v1 Announce Type: new Abstract: Low-precision Transformer systems increasingly quantize attention matrix multiplications, while softmax often remains at higher precision. During pretra