Search: “multimodal”

RFChipAgent: Multi-Agentic AI Flow for Analog/RF Chip Design

arXiv:2610.10858v1 Announce Type: cross Abstract: Analog/RF circuits remain the critical interface between digital computation and the physical world, and emerging standards from Wi-Fi 7 to 6G place s

agentsarxiv-cs-ai

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Softmax Attention on Gaussian Mixtures: Linear When It Can, Selective When It Must

DGX agent

arXiv:2610.11798v1 Announce Type: cross Abstract: Softmax attention, at the heart of Transformers, has demonstrated remarkable capabilities. Yet its underlying mechanisms remain only partially underst

tutorialsarxiv-cs-lg

9 Oct 2026

SuperNav: An Agentic Navigation System for Any Task in Any Scene

arXiv:2610.12126v1 Announce Type: cross Abstract: General-purpose service robots need navigation systems that can handle diverse human requests in unfamiliar environments, combining task generality wi

agentsarxiv-cs-cv

Hardware

The Operator Mismatch Problem: Deploying BEV Perception with Portable GPU Compute

arXiv:2610.11504v1 Announce Type: new Abstract: Modern autonomous driving systems rely on bird's-eye-view (BEV) perception models that fuse camera and LiDAR inputs to detect objects in 3D space. These

hardwarearxiv-cs-ai

TKCAM: Text and Keyframe to Camera Trajectory Generation

arXiv:2610.11105v1 Announce Type: new Abstract: Generating high-quality and controllable camera motion is essential for AI-assisted cinematography, video synthesis, and 3D scene understanding. We intr

Towards Unified Evaluation of Prompt Enhancers for Video Generation

arXiv:2610.11736v1 Announce Type: new Abstract: Modern video generators can realize increasingly complex visual narratives, positioning the prompt enhancer (PE) as a critical bridge from concise user

VICO: Visual Environments Co-Evolving for Vision-Language Model Reasoning

arXiv:2610.10782v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard recipe for post-training vision-language models (VLMs), but it typically a

researcharxiv-cs-ai

A Deafening Silence: Catastrophic Forgetting Lives in the Output Embeddings of Tokens the Data Never Speaks

model-releasesarxiv-cs-cl

arXiv:2610.09835v1 Announce Type: new Abstract: Continual pre-training and fine-tuning in Large Language Models (LLMs) inevitably induce catastrophic forgetting, typically mitigated by replay using of

A Lightweight Vision-Language Fusion Framework for Predicting App Ratings from User Interfaces and Metadata

arXiv:2602.20531v2 Announce Type: replace Abstract: App ratings are among the most significant indicators of the quality, usability, and overall user satisfaction of mobile applications. However, exis

BanglaRhet: Benchmarking Classical and Transformer Models for Rhetorical and Persuasion Detection in Bangla Political Speech

model-releasesarxiv-cs-cl

arXiv:2610.09464v1 Announce Type: new Abstract: Political discourse often uses rhetorical and persuasive language to frame narratives, influence public opinion, and mobilize audiences. While Bangla na

Benchmarking Behavioral Steerability in Behavior Foundation Models

model-releasesarxiv-cs-ro

arXiv:2610.10198v1 Announce Type: new Abstract: Behavior Foundation Models (BFMs) are emerging as a paradigm for translating human intentions into executable humanoid behaviors. As these models evolve

Bookkeeping, Composition, or Unreachable Gold? Reading MemoryAgentBench's Conflict-Resolution Scores Against a Frozen Last-Write Resolver

model-releasesarxiv-cs-cl

arXiv:2610.09193v1 Announce Type: cross Abstract: MemoryAgentBench's Conflict Resolution split is read as measuring 'selective forgetting'. We execute the benchmark's own rule - the newest statement a

Context-aware Attention-based Gaussian Mixture Models for Vehicular Trajectory Prediction

arXiv:2610.09174v1 Announce Type: new Abstract: Reliable and interpretable trajectory prediction is critical for cooperative and autonomous driving in complex and uncertain environments. This paper in

agentsarxiv-cs-lg

Decoding Neural Population Dynamics through Robotic Analog

arXiv:2610.09977v1 Announce Type: new Abstract: Animal evidence shows that precise voluntary movements arise from rotational neural population dynamics in motor cortex, but their physical effects rema

researcharxiv-cs-ro

emg2face: Expressive Facial Animation with High-Density Surface EMG

arXiv:2610.09304v1 Announce Type: cross Abstract: Facial movements convey subtle and important information that is critical for human social communication. Optical methods for face capture are difficu

End-to-End Autonomous Generation of Human Assembly Plans

arXiv:2610.09781v1 Announce Type: new Abstract: Turning a CAD design into an assembly plan is still largely done by hand, requiring engineers to reason about geometric feasibility, tool access, stabil

agentsarxiv-cs-ro

ExperienceIndex: Artifact-Grounded Memory

arXiv:2610.10091v1 Announce Type: new Abstract: Knowledge-intensive tasks require answering many questions by reasoning about a shared corpus of artifacts (e.g., court cases, or scientific literature)

agentsarxiv-cs-cl

FedSSMCoOp: SSM Encoders for light-weight Federated Prompt Learning for Few-shot Classification

arXiv:2610.09907v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong performance across a wide range of downstream vision tasks, thanks to the complementary information cont

safetyarxiv-cs-cv

Generative AI for Autonomous Driving: Frontiers and Opportunities

arXiv:2505.08854v2 Announce Type: replace Abstract: Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled cap

safetyarxiv-cs-cv

Mixture of Layers: Dynamic Layer Routing for Visual Reasoning

arXiv:2610.09440v1 Announce Type: new Abstract: Pre-trained vision encoders contain layer-wise visual representations that differ in spatial granularity, semantic abstraction, and sensitivity to local

Neural Sampling with Reweighted Normalizing Flows via the Wasserstein--Fisher--Rao JKO Scheme

arXiv:2610.10278v1 Announce Type: cross Abstract: We propose a neural algorithm for sampling from distributions specified by unnormalized Boltzmann densities. Our approach is based on the Jordan--Kind

researcharxiv-cs-lg

Prototype-Based Knowledge Guidance for Fine-Grained Structured Radiology Reporting

arXiv:2603.11938v2 Announce Type: replace-cross Abstract: Structured radiology reporting promises faster, more consistent communication than free text, but automation remains difficult as models must

Quantifying Volumetric Risk: Class-Aware Asymmetric Weighted Conformal Prediction for 3D Medical Image Segmentation

arXiv:2610.09392v1 Announce Type: new Abstract: Reliable volumetric segmentation is critical for clinical diagnostics, yet foundation models such as MedSAM remain deterministic and lack calibrated unc

Research on Deep Learning-Based Semantic Segmentation Algorithms for Subcortical Brain Structures

arXiv:1907.09194v3 Announce Type: replace-cross Abstract: Segmentation of subcortical brain structures is fundamental to computer-aided diagnosis and treatment in neurology and related clinical fields

Local Ai

RoboFAC: A Comprehensive Framework for Robotic Failure Analysis and Correction

arXiv:2505.12224v5 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have recently advanced robotic manipulation by translating natural-language instructions and visual observations

local-aiarxiv-cs-ro

Temporal Visuo-Tactile Learning for Dexterous Grasp Stability

arXiv:2610.10283v1 Announce Type: cross Abstract: Humans can grasp everyday objects with almost perfect success rates using fingertip tactile feedback, yet much of the robotic grasping literature emph

The Metagame of Interpretability and Meta-Attributions

arXiv:2605.06295v2 Announce Type: replace Abstract: How can an arbitrary attribution method be generalized from first principles to capture interactions? We answer this with the metagame, a conceptual

researcharxiv-cs-lg

Validity Without Ground Truth: What Stated-Preference Economics Offers the Evaluation of Language Models

arXiv:2610.10506v1 Announce Type: cross Abstract: Many of the questions now put to large language models have no correct answer to score against: what a policy is worth, which option a user should cho

safetyarxiv-cs-cl

VideoEvolve: Co-Evolving Memory and Retrieval for Long Video Understanding

arXiv:2610.10183v1 Announce Type: new Abstract: Long video understanding increasingly relies on external memory to organize massive visual streams into compact representations. However, most memory-ba

agentsarxiv-cs-cv

2D Spatial Reasoning with Adaptive Neural Cellular Automata

arXiv:2610.08518v1 Announce Type: new Abstract: Many modern learning approaches are still struggling with spatial reasoning tasks, i.e. they lack the ability to utilize geometric information of percei

A self-learning scientific agent for X-ray diffraction

arXiv:2610.07862v1 Announce Type: cross Abstract: A central challenge for scientific agents is to turn analytical experience into reusable expertise grounded in physical evidence. Here we introduce Ga

agentsarxiv-cs-ai

Aggregating User Preferences while Ensuring Equity, Diversity, and Inclusion using Graph Summarization

arXiv:2610.07128v1 Announce Type: cross Abstract: Aggregating the preferences of diverse user groups into a collective outcome raises fundamental challenges of equity, diversity, and inclusion (EDI):

safetyarxiv-cs-ai

Beyond Waypoint Regression: Query-Based Cost Learning over Reachable Ego Futures for End-to-End Driving

arXiv:2610.08123v1 Announce Type: cross Abstract: End-to-end planners based on waypoint regression achieve strong open-loop accuracy, but they primarily learn to mimic expert geometry and remain diffi

safetyarxiv-cs-ai

CoDe-LoRA: Mitigating the Orthogonality Dilemma in Continual Learning of LLMs via Knowledge Consolidation and Decoupling

arXiv:2610.08312v1 Announce Type: new Abstract: Continual learning (CL) is essential for Large Language Models (LLMs) to sequentially adapt to evolving tasks. To mitigate catastrophic forgetting, rece

EPOCH: Reliable Discovery through Evidence-Governed Search

arXiv:2610.06986v1 Announce Type: new Abstract: AI research agents are increasingly used to search over programs, mathematical constructions, and proofs. However, existing systems typically optimize e

Applications

EVFormer: An Egocentric Vision-EMG Bidirectional Attention Model for Bimanual Hand Pose Estimation

arXiv:2610.06970v1 Announce Type: new Abstract: Egocentric bimanual hand pose estimation is important for virtual interaction, wearable control, and rehabilitation, but visual observations are often d

applicationsarxiv-cs-lg

FreDF: Learning to Forecast in the Frequency Domain

arXiv:2402.02399v3 Announce Type: replace-cross Abstract: Time series modeling presents unique challenges due to autocorrelation in both historical data and future sequences. While current research pr

safetyarxiv-cs-ai

GeoPID: Decomposing and Steering Visual Information in Vision-Language Models

arXiv:2610.08401v1 Announce Type: cross Abstract: While recent vision-language models (VLMs) have shown outstanding performance across diverse applications, they tend to under-use visual information a

How Much Planning Is Enough? Reducing Search and Computation in World-Model Planning

arXiv:2610.08350v1 Announce Type: cross Abstract: Visual world models enable goal-directed control through decision-time action search, but their deployment efficiency is often limited by conservative

researcharxiv-cs-ai

Knee3DVLM: Dual-Sequence Full-Volume Vision-Language Modeling for Comprehensive Knee MRI Assessment

arXiv:2610.08482v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly being applied to three-dimensional medical imaging, but their application to knee MRI remains limited,

Knowing When to Trust a Prior: Reliability-Gated Cue Fusion for Video Gaze Prediction

arXiv:2610.08663v1 Announce Type: new Abstract: Video gaze prediction is led by gaze-trained models, yet gaze-free priors carry signal those models have not absorbed, if one knows when to trust them.

Logbook: Extremely Long-form Audio Event Understanding

arXiv:2610.07338v1 Announce Type: cross Abstract: Audio benchmarks are built around short, pre-segmented clips, limiting model design to brief inputs or fixed vocabularies. To close this gap, we intro

Applications

Low-Rank and Structured Sparse Tensor Decomposition for Anomaly Detection in Multivariate Functional Data

arXiv:2610.06930v1 Announce Type: cross Abstract: Multivariate functional data arise in many modern manufacturing systems, where multiple sensors record densely sampled process trajectories. Monitorin

applicationsarxiv-cs-lg

Local Ai

MacJEPA: Missingness-Robust Audio-Visual Recognition from Untrimmed Egocentric Videos

arXiv:2610.08192v1 Announce Type: new Abstract: Audio-visual models improve egocentric action recognition by exploiting complementary cues, yet typically assume that both streams remain available at i

local-aiarxiv-cs-cv

Mathematical Invariant-Enabled Topological Neural Networks for Molecular and Materials Property Prediction

arXiv:2610.07712v1 Announce Type: cross Abstract: Existing molecular and materials learning approaches often rely on a limited set of structural representations, which may capture only selected aspect

researcharxiv-cs-lg

Navigation with RF Cues: Embodied Perception Action under Multipath Uncertainty

model-releasesarxiv-cs-ro

arXiv:2610.08105v1 Announce Type: new Abstract: Smart factory inspection requires robots to reach connected equipment without a prior map or known target coordinates. Radio frequency (RF) signals from

Tutorials

OxiGen: Oxidation-State-Aware Crystal Generation

arXiv:2610.08296v1 Announce Type: new Abstract: Generative models have the potential to accelerate inorganic materials discovery by enabling inverse design, but generating experimentally realisable cr

tutorialsarxiv-cs-lg

PACE: Stage-Consistent Long-Horizon Robot Manipulation via Progress-Aligned Context for Execution

arXiv:2610.07917v1 Announce Type: new Abstract: Demonstration-conditioned policies provide a natural interface for specifying robot behavior, yet long-horizon manipulation remains difficult when visua

safetyarxiv-cs-ro