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VEDJE: Video-Efficient Discriminative Joint Encoder for Scalable Video-Text Retrieval

arXiv:2610.11850v1 Announce Type: new Abstract: Finding the right video often requires distinguishing similar scenes in which different events occur. Joint matching improves retrieval, but processing

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Velocity Scaling in Flow Matching

DGX agent

arXiv:2610.10823v1 Announce Type: new Abstract: Scaling a learned flow-matching velocity field v_heta by a gain gamma(t) was recently shown to greatly improve generation quality. Prior work argued tha

researcharxiv-cs-cv

9 Oct 2026

Verification with Transfer: Exact Information Frontiers and Their Price in Calls

arXiv:2610.12211v1 Announce Type: new Abstract: A verifier that accepts or rejects whole answers reveals little: under a flat prior over k-bit answers, zero error needs 2^k-1 verifications. The usual

VersaCamVLA: Camera-Configurable VLA Policies for Robotic Manipulation

arXiv:2610.12451v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as powerful foundations for robotic manipulation, but their reliance on fixed camera configurations dur

VesselSDF: Distance Field Priors for Vascular Network Reconstruction

arXiv:2506.16556v2 Announce Type: replace-cross Abstract: Accurate segmentation of vascular networks from sparse CT scan slices remains a significant challenge in medical imaging, particularly due to

VESSI - VLM-Enhanced Support for Surveillance and Investigations

arXiv:2610.11674v1 Announce Type: new Abstract: Automated video surveillance analysis has become a critical component of intelligence infrastructures and Law Enforcement agencies. Traditional systems

VFold: Symmetry-Aware Cross-Layer Value Cache Compression

arXiv:2610.12338v1 Announce Type: new Abstract: While caching key-value (KV) states accelerates Large Language Model (LLM) decoding, this cache can dominate memory usage at long context lengths. One s

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

VINCIE-NExT: Unlocking Video Editing from Images via In-Context Modeling

arXiv:2610.12104v1 Announce Type: cross Abstract: Building a capable video editor remains significantly harder than a video generator: editing requires (source, instruction, edited) triplets that are

What is the goal of unsupervised machine learning?

arXiv:2610.11697v1 Announce Type: new Abstract: Unsupervised learning is one of the main branches of machine learning. Here I argue that unlike the other branches of machine learning (supervised and r

When AI Finds Hidden Messages, Does It Report?

arXiv:2610.10620v1 Announce Type: cross Abstract: When an assistant encounters a message for another AI, does it tell its user? Four fixed model-provider deployments perform simulated source tasks in

When Can You Prune Your Network? A Study of Intermediate Neurons in Multilingual Speech Parsing

arXiv:2610.11520v1 Announce Type: new Abstract: End-to-end speech parsing, a task recently proposed, consists in predicting both the transcription and the syntactic tree for a spoken utterance. Existi

When Has a Bayesian Neural Network Sampled Enough? Adaptive Inference Time with Statistical Guarantees

arXiv:2610.12212v1 Announce Type: new Abstract: Bayesian neural network predictions are commonly approximated using a fixed number of Monte Carlo samples per input, without controlling the resulting e

When Lower Reconstruction Loss Hurts: Distributionally Robust Refinement for Low-Bit LLM Quantization

arXiv:2610.11226v1 Announce Type: new Abstract: Weight-only post-training quantization (PTQ) relies heavily on reconstruction loss minimization to preserve model quality at low precision. We show that

Where Draft Trees Lose Target Mass: Exit-Guided Speculative Decoding

arXiv:2610.11750v1 Announce Type: new Abstract: Tree-based speculative decoding verifies multiple draft continuations in one target-model pass, but finite trees built from draft scores face a fundamen

Why machines will still not rule the world

arXiv:2610.11424v1 Announce Type: new Abstract: In our book Why machines will never rule the world [13, 14] we argue that arti- ficial general intelligence is mathematically impossible. This is becaus

Wieszcz-XIX: A 3.1-Billion-Word Corpus of Pre-1918 Polish and Temporally Bounded Language Models Trained From Scratch

arXiv:2610.10592v1 Announce Type: new Abstract: Historical Polish is well documented as a language but annotated in machine-readable form only to about a million words for the period this paper covers

WorldCraft: From Camera Navigation to Object Manipulation in Interactive Video World Models

arXiv:2605.25077v2 Announce Type: replace Abstract: Recent video world models enable interactive camera navigation but provide limited control over individual objects. We study persistent object-state

WorldGuide: Goal-Directed Video World Model for Procedural Task Execution

arXiv:2610.12459v1 Announce Type: new Abstract: Video generators and video-based world models can synthesize plausible visual trajectories, but long-horizon procedural tasks require generation to adap

Writing for the Reviewer: Defensive Writing in GPT Models

arXiv:2610.11355v1 Announce Type: new Abstract: Researchers increasingly use ChatGPT to revise their papers, and recent GPT versions often narrow or even retract the authors' claims. We call such chan

YOCO: You Only Calibrate Once! Fast Mocap Calibration for Dexterous Teleoperation

arXiv:2610.11657v1 Announce Type: new Abstract: Dexterous teleoperation requires reliable human-hand state estimations. However, common low-cost motion-capture gloves and markerless trackers often exh

Zatom-2: Multitask Pretraining on Atomistic Data for Generative Modeling across Domains

arXiv:2610.11454v1 Announce Type: cross Abstract: Unified atomistic modeling has the potential to accelerate discovery in chemistry, materials science, and biology by bridging data-rich chemical domai

A conceptual framework for ideology in online discourse beyond the left and right

arXiv:2603.18945v2 Announce Type: replace-cross Abstract: Computational social science (CSS) has largely operationalized ideology along a single left/right partisan axis when studying online discourse

A Deterministic Evidence Layer for Vision-Language Autism Screening from Naturalistic Home Video

arXiv:2610.09217v1 Announce Type: new Abstract: Autism spectrum disorder (ASD) is diagnosed through specialist observation of a child's social behavior, and access to that expertise is the bottleneck

A Geometry-Based Capacity Theory for Finite-Feature Associative Memory

arXiv:2610.09056v1 Announce Type: new Abstract: We develop a geometry-based capacity theory for exact-key retrieval in compressed finite-feature Hebbian associative memory. For random or approximately

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

A method for multimodal analysis of TAIGA experiment data using essential features

arXiv:2610.08985v1 Announce Type: cross Abstract: The aim of processing and analyzing experimental data from physical experiments is to obtain physically significant information about the phenomenon u

A prism hierarchy of learning regimes in large linear autoencoders

arXiv:2606.05335v2 Announce Type: replace Abstract: Theoretical studies of machine learning models commonly consider different limiting regimes in which the learning dynamics of gradient descent becom

A Proof-of-Concept Study of Weakly Supervised Labeling of Fine-Grained EEG Components for Artifact Attenuation

arXiv:2610.09792v1 Announce Type: new Abstract: Electroencephalography (EEG) is highly susceptible to electromyographic (EMG) artifacts, whose temporal heterogeneity and spatial-spectral overlap with

A Self-Pruning Transformer: Extreme KV-Cache Compression with Universal Attention

arXiv:2610.09051v1 Announce Type: new Abstract: The large KV-cache size of modern LLMs creates a barrier to efficient deployment. Recent work has explored replacing attention layers' RoPE positional e

A Unified Kinematic Representation Enables Reusable Biological Joint Moment Estimation

arXiv:2610.09150v1 Announce Type: new Abstract: Objective: Data-driven models that estimate physiological states, particularly biological joint moments, are widely used in exoskeleton control. However

A Vehicle-Integrated Approach to Digital Twin Deployment for Bridges Through Drive-By Sensing

arXiv:2610.08822v1 Announce Type: new Abstract: Ageing bridge infrastructure is a growing global concern, yet conventional Structural Health Monitoring (SHM) systems are costly and difficult to scale,

Abdominal Ultrasound Simulation from Semantic Labels using Paired Label-to-Physics-Based Image Translation

arXiv:2610.08849v1 Announce Type: cross Abstract: Purpose: Current abdominal ultrasound (US) simulation methods often require CT-based anatomical references for ray-casting, limiting deformation and p

AdaPS-LiNGAM: Adaptive Predecessor Selection for Linear Non-Gaussian Acyclic Models under Small-Sample Settings

arXiv:2610.09782v1 Announce Type: new Abstract: Causal discovery becomes particularly challenging when the available sample size is small relative to the number of variables. This challenge also arise

Adaptive Code Generation for Controlling Robots

arXiv:2610.09588v1 Announce Type: new Abstract: Deploying robots as Complex Adaptive Systems (CAS) in unknown and dynamic environments necessitates a transition from rigid command libraries toward int

Adaptive Visual Token Reduction for Accelerated Image Understanding

arXiv:2610.09252v1 Announce Type: new Abstract: Large Vision-Language Models achieve strong VQA performance, but processing high-resolution, information-rich images requires substantial computation, m

AI breakthroughs in robotics won’t change your life any time soon

The story is a collaboration between MIT Technology Review and Aventine, a non-profit research foundation that creates and supports content about how technology and science are changing the way we liv

researchmit-tech-review

An Accuracy--Information Tradeoff for Loss-Difference Conditional Mutual Information

arXiv:2610.09206v1 Announce Type: new Abstract: Loss-difference conditional mutual information (ld-CMI) uses the smallest of the standard observations in the supersample hierarchy of generalization bo

An AI-assisted conditioning and geological interpretation workflow for usage in implicit geological modeling

arXiv:2610.09871v1 Announce Type: cross Abstract: Implicit modeling and Relative Geologic Time are geological modeling techniques that enable more efficient, faster, less biased and more reproducible

An extended deep energy method for thermo-mechanical crack propagation

arXiv:2610.09433v1 Announce Type: new Abstract: Thermo-mechanical fracture couples transient heat conduction on a cracked domain with a crack that grows as the temperature and the displacement evolve.

Announcing ARC Prize Research Summit 2026 Research Speaker Kevin Murphy @sirbayes is a research scientist at Google DeepMind and author of t…

researchfrancois-chollet--x

Announcing ARC Prize Research Summit 2026 Research Speaker Kevin Murphy @sirbayes is a research scientist at Google DeepMind and author of the “Probabilistic Machine Learning” textbooks, developing AI

Attention-Mass Condensation for Sparse Decoding

arXiv:2602.06317v3 Announce Type: replace-cross Abstract: Attention-mass concentration creates an opportunity for sparse decoding, but retained mass alone does not guarantee a stable greedy decision:

Attention via Black-Box Vector Search

arXiv:2610.10135v1 Announce Type: cross Abstract: Sparse attention mechanisms estimate attention over n tokens using a small subset of keys. Many existing approaches use maximum inner product search (

Backdooring Acoustic Foundation Models for Physically Realizable Triggers

arXiv:2610.09819v1 Announce Type: cross Abstract: Acoustic foundation models (AFMs) have democratized acoustic applications, enabling powerful models for tasks ranging from speech recognition to speak

Batch Augmentation with Unimodal Fine-tuning for Multimodal Fusion of Large Language Models

arXiv:2505.06592v2 Announce Type: replace Abstract: In this paper, we propose batch augmentation with unimodal fine-tuning for multimodal learning. We start with pre-trained unimodal models. We fine-t

BeatFlow-ECG: Rectified Flow for ECG Reconstruction from Indirect Wearable Signals

arXiv:2610.09052v1 Announce Type: new Abstract: Continuous cardiac monitoring outside clinical settings requires signals that are both informative and practical to collect during daily life. Electroca

Belief-Space Planning with Planner-Conditioned Estimator Error under Intermittent Observations

arXiv:2610.09207v1 Announce Type: new Abstract: Belief-space planners with separately designed or off-the-shelf estimators may have access to state-relevant information the estimator does not observe.

Benign Overfitting under Heterogeneous Input Fusion

arXiv:2610.09340v1 Announce Type: new Abstract: Benign overfitting is extensively studied when learning from a single high-dimensional input, but its behavior under heterogeneous input fusion remains