Search: “context”

RecastVLA: From Past Interaction to Future Control with Adaptive Policy States

arXiv:2609.32155v1 Announce Type: new Abstract: Sequential manipulation requires a robot to track what has already happened, even when the current scene no longer reveals it. Policies with explicit hi

safetyarxiv-cs-ro

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Refinement Symmetry in Multimodal Transformers

DGX agent

arXiv:2609.32669v1 Announce Type: cross Abstract: Attention weights depend on token counts, which change with the representation of a signal. We study refinement symmetry: splitting a representation w

researcharxiv-cs-cv

29 Sept 2026

Relevance Does Not Imply Applicability: Experience Activation for Personal GUI Agents

arXiv:2609.33304v1 Announce Type: new Abstract: Personal Graphical User Interface (GUI) agents rely on interaction history to infer what a user wants from ambiguous instructions and to anticipate recu

RepFlow: Reciprocal Supervision Improves Generation and Representation in Flow Models

arXiv:2609.33217v1 Announce Type: new Abstract: Generative models learn visual structure through denoising, yet their internal states are entangled with both noise level and network depth, making it d

Rethinking Latent Visual Reasoning: Grounding Latent Reasoning in Visual Evidence

arXiv:2609.34563v1 Announce Type: new Abstract: Latent visual reasoning (LVR) enables multimodal large language models (MLLMs) to perform intermediate computation in continuous latent tokens rather th

Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios

arXiv:2609.35086v1 Announce Type: new Abstract: In this work, we study portfolio optimization under the stochastic discount factor (SDF) framework by learning market state representations that capture

Retrieved but Not Delivered: Multimodal Memory Delivery for Long-Term Agents

arXiv:2609.32590v1 Announce Type: new Abstract: Work on memory for multimodal agents optimizes what is written, updated and retrieved. Between retrieval and the answer, however, is a stage that multim

agentsarxiv-cs-cv

Local Ai

Revisit to Segment: Working Memory Distillation for Reasoning Segmentation

arXiv:2609.34863v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have approached image segmentation by reasoning about visual content and predicting target locations. Their gen

local-aiarxiv-cs-cv

RoPE is Dead, Long Live RoPE: Towards Scalable Data-aware Positional Encodings

arXiv:2609.34556v1 Announce Type: cross Abstract: Transformers process tokens without any inherent notion of order, making positional encoding a fundamental requirement rather than an architectural re

ROTE: Benchmarking Neural Memorization on Complexity-Controlled Symbolic Sequences

arXiv:2609.31918v1 Announce Type: new Abstract: We introduce ROTE (RollOut Testing of Exact memorization), a benchmarking protocol for evaluating symbolic memorization of neural architectures. We stud

SceneScaffold: Active Scene-State Construction for Unified 3D Scene Understanding

arXiv:2609.33518v1 Announce Type: new Abstract: Recent 3D large multimodal models (3D-LMMs) rely on a visual bottleneck to compress complex 3D scene evidence into a limited number of visual tokens com

researcharxiv-cs-cv

Scoring the Wrong Question: Readout Failures in Constrained-Option Evaluation

arXiv:2609.33179v1 Announce Type: cross Abstract: Constrained-option scoring reads a model's probabilities for a fixed set of permitted answers, so it returns a score even when the model is about to w

SegBanana: Steering Unified Multimodal Models into Medical Segmenters

arXiv:2609.34235v1 Announce Type: new Abstract: Medical image segmentation remains challenging in practical deployment, as models often struggle to generalize beyond the distributions covered by their

agentsarxiv-cs-cv

Self-Evolutionary Replanning for Failure-Aware Motion Planning

model-releasesarxiv-cs-ro

arXiv:2603.02772v2 Announce Type: replace Abstract: Motion planners tuned under nominal conditions can fail when execution conditions change. Existing differentiable adaptation methods provide efficie

Separating personal from population gains when calibrating EEG foundation models for new users

arXiv:2609.34801v1 Announce Type: new Abstract: Foundation models are increasingly adapted to individual users, but an apparent personalization gain can simply reflect a stronger population model. Thi

SetOPD: From Few Visual Exemplars to Multimodal Candidate Sets for Remote-Sensing Open-Prompt Detection

arXiv:2609.32529v1 Announce Type: new Abstract: Open-prompt detectors allow users to specify targets with text, visual exemplars, or both. We argue that existing designs underuse the visual modality i

researcharxiv-cs-cv

SpecRegMatch: Robust Semi-Supervised Regression for Vehicle Interior Noise Prediction

arXiv:2609.34111v1 Announce Type: cross Abstract: The rapid advancement of artificial intelligence has observed increased application in predicting vehicle interior noise levels within the automotive

researcharxiv-cs-cv

StarBOA: Real-Time Mamba State-Space Unrolling for Sparse Radar Micro-Doppler in ISAC Networks

arXiv:2609.33408v1 Announce Type: new Abstract: In Integrated Sensing and Communications (ISAC), radar sensing must operate under chirp subsampling with up to 90% missing data. An attention-based base

SyncRA: Learning Temporal Correspondence in Omni-Modal Models

model-releasesarxiv-cs-cv

arXiv:2609.34363v1 Announce Type: new Abstract: Recent omni-modal models demonstrate strong perception of audio and visual inputs, yet often struggle to connect what they hear with what they see at th

TANGO: Watermarking Masked Diffusion Language Models in Token Pairs

arXiv:2609.35224v1 Announce Type: new Abstract: Masked-diffusion language models fill in masked positions in parallel and in no fixed order. Most practical text watermarks assume left-to-right generat

Teach Yourself Where to Look: On-Policy Attention Self-Distillation for Reasoning

arXiv:2609.33200v1 Announce Type: new Abstract: On-policy self-distillation trains reasoning models on their own trajectories using dense token distribution guidance from a privileged teacher with acc

Temporal Heterogeneous Graph Pretraining for Relational Deep Learning

arXiv:2609.35219v1 Announce Type: new Abstract: Relational deep learning models database rows and foreign-key links as a heterogeneous graph for prediction from record attributes and relational contex

Local Ai

Towards More Trustworthy and Interpretable LLMs for Code through Syntax-Grounded Explanations

arXiv:2407.08983v2 Announce Type: replace-cross Abstract: Trustworthiness and interpretability are inextricably linked concepts for LLMs. The more interpretable an LLM is, the more trustworthy it beco

local-aiarxiv-cs-lg

Transform-Aligned Learned Features for Lossy Point Cloud Attribute Compression

model-releasesarxiv-cs-cv

arXiv:2609.34834v1 Announce Type: new Abstract: Transform-based methods provide an effective framework for point cloud attribute compression by representing attributes as transform coefficients. Intro

TriDrive: Joint Driver, Vehicle, and Road Modeling for Forecasting and Driver Monitoring

model-releasesarxiv-cs-cv

arXiv:2609.33000v1 Announce Type: cross Abstract: Predicting how drivers, vehicles, and road scenes interact and evolve together is central to driver monitoring. Prior work models in-cabin activity or

Uncertainty Quantification in Cardiac Model Personalisation from Ultrafast Ultrasound

arXiv:2609.35214v1 Announce Type: cross Abstract: Cardiac model personalisation requires inferring mechanical parameters that are not directly measurable in vivo. Ultrafast ultrasound shear wave elast

Uni-VLaT: Whole-Body Tactile Adaptation of VLA Policies for Humanoid Loco-Manipulation

arXiv:2609.35450v1 Announce Type: new Abstract: Physical contact often determines how a humanoid should respond during loco-manipulation, yet vision and proprioception alone are often insufficient to

tutorialsarxiv-cs-ro

Universal Approximation of Measure-to-Measure Operators by Pushforwards

arXiv:2609.35483v1 Announce Type: new Abstract: Many learning tasks map an input distribution to an output distribution. A natural way to model such an operator is to transform each input sample using

Local Ai

VisionHOPE: Visual Backbones as Self-Modifying Learning Systems

arXiv:2609.33325v1 Announce Type: new Abstract: Visual backbones have evolved from Convolutional Neural Networks (CNNs) with local aggregation to Vision Transformers (ViTs) with global interactions, S

local-aiarxiv-cs-cv

VPTwin: Real-Sim-Real Video Prediction for Robotic Manipulation Planning

arXiv:2609.33104v1 Announce Type: new Abstract: While action-conditioned video prediction provides an intuitive world model for robotics, purely data-driven predictors often suffer from compounding er

tutorialsarxiv-cs-ro

Watch the Model Think: On-Policy Extraction of Activation Steering Vectors

arXiv:2602.14143v2 Announce Type: replace Abstract: When a model solves a problem on one attempt and fails it on the next, what separates the two is rarely the final answer token; it is the trajectory

What masking geometry works best for EEG foundation models?

arXiv:2609.33487v1 Announce Type: new Abstract: EEG foundation models hold promise for scalable brain-signal decoding across clinical and cognitive neuroscience applications, yet their pre-training pi

What Should a Streaming Video Model Remember?

arXiv:2606.16353v2 Announce Type: replace Abstract: Streaming video understanding models must answer queries at any moment during an ongoing stream, using only what they have observed so far and under

tutorialsarxiv-cs-cv

When Helpful Text Hurts: Option-Redirecting Bias in Vision-Language Models

arXiv:2609.32489v1 Announce Type: cross Abstract: In tri-modal visual question answering (VQA), auxiliary text is commonly used to complement visual and textual inputs, yet its reliability is often un

When Known Physics Helps Neural PDE Models: Residual Constraints Out-Regularize Generic Priors for Nonlinear Dynamics

arXiv:2609.34012v1 Announce Type: new Abstract: Neural PDE surrogates increasingly incorporate structural priors, yet it is often unclear whether their gains arise from physics-specific information or

Applications

When Should the Count Change? Learning State Maintenance for Causal Video Counting

arXiv:2609.35416v1 Announce Type: new Abstract: Continuous video counting requires distinguishing new observations from new objects or completed events. We introduce StaMina (State Maintenance), which

applicationsarxiv-cs-cv

Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation

arXiv:2603.01375v2 Announce Type: replace-cross Abstract: Test-time policy adaptation for multi-turn interactions (T2PAM) is essential for aligning Large Language Models (LLMs) with dynamic user needs

Hardware

WorldAttention: An Efficient Attention Architecture for Interactive Video World Models

arXiv:2609.34606v1 Announce Type: new Abstract: Leveraging the paradigm of autoregressive diffusion, text-conditioned interactive video world models aim to simulate temporally coherent environments gu

hardwarearxiv-cs-cv

A Survey on Fake Review Detection: From Pre-trained Language Models to Large Language Models

model-releasesarxiv-cs-ai

arXiv:2609.30292v1 Announce Type: cross Abstract: Online reviews shape consumer decisions, platform governance, and corporate reputation.Fake reviews compromise this information channel by injecting d

A Unified Account of Concepts and Chunks

arXiv:2609.30414v1 Announce Type: cross Abstract: Cognitive psychology has studied how people encode, use, and learn concepts that describe categories, and how they represent, recognize, and acquire c

tutorialsarxiv-cs-ai

ActKV: Efficient LLM Agents through Action-Guided KV Cache Management

arXiv:2609.31395v1 Announce Type: cross Abstract: Agentic LLM inference accumulates long KV caches across iterative observation-reasoning-action loops, imposing substantial memory overhead and limitin

agentsarxiv-cs-ai

Adapting for AI: How elementary teachers adjust their practices for an AI-integrated curriculum

arXiv:2609.31569v1 Announce Type: cross Abstract: Conversational AI tools are entering children's everyday experiences, and schools are interested in adopting them. However, successful classroom integ

researcharxiv-cs-ai

AFA-Net: A Differential Attention Approach for Auditory Attention Detection

arXiv:2609.31402v1 Announce Type: cross Abstract: Auditory Attention Detection (AAD) utilizes electroencephalographic (EEG) signals to identify a target speaker in a multi-speaker environment. Despite

An End-to-End Pipeline for Causal ML with Continuous Treatments: An Application to Financial Decision Making

arXiv:2609.30396v1 Announce Type: cross Abstract: This paper presents an end-to-end causal machine learning (ML) pipeline designed for real-world applications with continuous treatments. The proposed

Augmented Reality Interfaces for Human-Robot Collaboration: Development of a ROS 2-Based Sensor Streaming Framework and Validation via SLAM Algorithms

arXiv:2609.31396v1 Announce Type: new Abstract: In recent years, Human-Robot Collaboration (HRC) has taken on a central role in Industry 4.0 and collaborative robotics, demanding communication channel

researcharxiv-cs-ro

Aurora-X: Built for Extreme Time Series Forecasting

arXiv:2609.31038v1 Announce Type: new Abstract: Time series foundation models (TSFMs) enable cross-domain forecasting, but their development as general-purpose forecasters remains constrained by under

tutorialsarxiv-cs-lg

AuthGuard-R: Safety-Compliant Mission Hijacking and Dual-Gate Defense for LLM-Controlled Robots

model-releasesarxiv-cs-ro

arXiv:2609.31110v1 Announce Type: new Abstract: Large language models are increasingly used as high-level planners for mobile robots, robot manipulators, and autonomous vehicles. Recent studies show t

Beyond Approved Actions: Runtime Validation of Persistent Outcomes in Agent Workflows

arXiv:2609.31301v1 Announce Type: cross Abstract: Large language model agents increasingly act on software systems, no longer merely generating text but also changing databases and online services. Ho

agentsarxiv-cs-ai