research

STORK: Spatio-Temporal Observation of uterine contRactions via neural networKs

arXiv:2610.09598v1 Announce Type: new Abstract: Uterine contractions in fetal MRI are typically identified manually and discarded, limiting insights into contraction dynamics. We formalize Uterine Con

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StoryBlender: Inter-Shot Consistent and Editable 3D Storyboard with Spatial-temporal Dynamics

DGX agent

arXiv:2604.03315v2 Announce Type: replace Abstract: Storyboarding is a core skill in visual storytelling for film, animation, and games. However, automating this process requires a system to achieve t

researcharxiv-cs-cv

8 Oct 2026

STRIDE: Spatial-Temporal Representation for Interval-conditioned Disease Evolution in Longitudinal Glioblastoma MRI

arXiv:2610.08848v1 Announce Type: cross Abstract: Glioblastoma (GBM), an aggressive primary brain tumor, is routinely monitored with longitudinal MRI after treatment. Distinguishing stable disease (SD

Structure alone supports efficient visual computation in the Drosophila visual system

arXiv:2610.10023v1 Announce Type: cross Abstract: Understanding the extent to which measured synaptic wiring determines computation remains a central challenge. Here, we couple the proofread adult Dro

StyleFields: Multi-Scale AdaIN-Modulated Implicit SDFs for Coarse-to-Fine 3D Shape Reconstruction and Editing

arXiv:2610.09200v1 Announce Type: new Abstract: We introduce StyleFields, a DeepSDF-based architecture for high-fidelity 3D reconstruction that enables controllable geometric style mixing: the coarse

Tactile Reconstruction of Contact Task Frames and Forces for Hybrid Force/Motion Control

arXiv:2610.10020v1 Announce Type: new Abstract: Hybrid force/motion control requires knowledge of the interaction force and of a task frame defining the force- and motion-controlled directions. These

researcharxiv-cs-ro

Talking with Language Models

arXiv:2610.09064v1 Announce Type: cross Abstract: When we interact with large language models (LLMs), are we having a conversation? They are designed to invite us to treat them as intelligent interloc

Task-Sufficient Contraction: Source Selection for Machine Information Interfaces

arXiv:2610.08884v1 Announce Type: cross Abstract: A declared task can sometimes certify a reduced source before a downstream encoder, codebook, rate, distortion target, or optimizer is chosen. This pa

Temporal Predictive Multiplicity: Equally Accurate Time Series Models Yield Different Forecast Trajectories

arXiv:2610.09994v1 Announce Type: new Abstract: Models with near-identical predictive performance can yield substantially different predictions, a phenomenon known as predictive multiplicity. Prior wo

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

Tetris3D: 3D Scene Generation With Objects That Fit Together

arXiv:2610.10539v1 Announce Type: new Abstract: We propose Tetris3D, a generative framework for single-image 3D scene reconstruction that recovers objects which are physically and geometrically cohere

The Cost of Long Memory: State, Context, and Stability Complexity in Sequence Models

arXiv:2610.08816v1 Announce Type: new Abstract: Long-range temporal dependence poses a resource question for sequence models: for a specified predictive-memory law, how much state, context, or dynamic

The Download: AI roadblocks for humanoids and portable rubber dams

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. AI breakthroughs in robotics won’t change your life any time s

researchmit-tech-review

The Identifiability and Observability of Deep Normalized Attention

arXiv:2610.09620v1 Announce Type: new Abstract: We study which parameters of deep, unmasked, single-head attention are determined by its input--output function. For known positive nonconstant real-ana

The Impact of Likelihood Tempering on the Limiting Predictive Moments of Variational Bayesian Linear Neural Networks

arXiv:2610.09132v1 Announce Type: cross Abstract: In wide Bayesian neural networks, Gaussian mean-field variational inference is prone to 'prior dominance': the Kullback-Leibler (KL) regularization te

The IroyinSpeech Text Corpus: 24,905 Curated Yoruba Sentences for Speech and Language Technology

arXiv:2610.05366v2 Announce Type: replace Abstract: IroyinSpeech is a 42-hour, 80-speaker Yoruba read-speech corpus whose audio has been distributed by ELRA since 2024. This paper describes the releas

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

The Silhouette Operator: Identifiability of Low-Rank Measures from One-Dimensional Projections

arXiv:2610.09687v1 Announce Type: cross Abstract: Structured recovery phenomena, such as restricted isometry properties in compressed sensing, have shown that high-dimensional objects can often be rec

Think Before You Paint: Recursive Latent Reasoning for Diffusion Models

arXiv:2610.09876v1 Announce Type: cross Abstract: Diffusion models generate realistic images but often fail on visual reasoning tasks, such as filling in a Sudoku or drawing the path through a maze. W

Thinking in Depth: Retrospective Inference for Tabular Foundation Models

arXiv:2610.10317v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are pretrained across diverse tabular tasks and make predictions on a new table at inference time using its labeled exa

Tiny-Scale Chinese BERT Pretraining: A Controlled Comparison of MLM, WWM, and MacBERT Strategies

arXiv:2610.08879v1 Announce Type: new Abstract: Pretraining strategies significantly impact the quality of language models, yet existing comparisons of Masked Language Modeling (MLM), Whole Word Maski

TIRA: Tumor Immune Representation Adaptation for Zero-Shot Cross-Cancer MSI and TMB Prediction

arXiv:2610.09441v1 Announce Type: new Abstract: Microsatellite instability-high (MSI-H) and high tumor mutational burden (TMB-H) are clinically relevant biomarkers, yet their histopathological predict

Towards Calibrated Probabilistic Forecasts for Events of Interest via Outcome-Conditional Recalibration

arXiv:2610.10076v1 Announce Type: cross Abstract: Calibration is an essential requirement for probabilistic predictions to be useful for decision making. While state-of-the-art prediction methods ofte

Towards Explaining Query Expansion Performance in Information Retrieval

arXiv:2610.09724v1 Announce Type: cross Abstract: Query Expansion (QE) techniques have long been widely used in Information Retrieval (IR) to address the vocabulary mismatch problem. They remain relev

TR-PTQ: High-Accuracy Integer-Only Transformer Post Training Quantization via Taylor Region Reformulation

arXiv:2610.09969v1 Announce Type: new Abstract: Post-training quantization (PTQ) enables efficient deployment, yet transformer architectures remain challenging to quantize due to nonlinear layers. Whi

Tracing Inputs, Verifying Outputs: Validating Attribution in Music Generation

arXiv:2610.09637v1 Announce Type: cross Abstract: How can we verify whose music contributed to an AI-generated output? This paper demonstrates how input-based attribution can provide verifiable eviden

Tri-Prompting: Video Diffusion with Unified Control over Scene, Subject, and Motion

arXiv:2603.15614v2 Announce Type: replace Abstract: Recent video diffusion models achieve strong visual quality and temporal coherence, but still lack coordinated control over scene layout, customized

Tucker Bottleneck Attention for Multi-Dimensional Sequence Modeling

arXiv:2610.09090v1 Announce Type: new Abstract: The quadratic cost of self-attention limits scalability to long sequences from multidimensional data. We introduce Tucker bottleneck attention (TuBA), w

Twist Flow for Inverse Problems

arXiv:2610.09281v1 Announce Type: new Abstract: In Bayesian inverse problems, posterior sampling requires generating samples that are consistent with given observations while capturing the range of pl

U-Space: Uncovering When and Why Uncertainty Arises in Language Models

arXiv:2610.09087v1 Announce Type: new Abstract: Large language models are informing decisions with ever-higher stakes. As the consequences of their errors grow, a central question becomes harder to ig

Unbounded Characteristic and Universal Kernels

arXiv:2610.09731v1 Announce Type: cross Abstract: Kernel methods are among the most powerful tools in machine learning and statistics, with a large number of successful applications. Their immense suc

UniCSI Towards a Universal Wi-Fi CSI Encoder for Ubiquitous Human Sensing

arXiv:2610.09559v1 Announce Type: new Abstract: Wi-Fi sensing promises to turn the everyday wireless signals that already surround us into ubiquitous sensors for human sensing. However, a fundamental

Unified Multi-plane Autoregressive Diffusion for 3D Multi-contrast MRI Synthesis

arXiv:2610.09376v1 Announce Type: new Abstract: Acquiring a complete set of magnetic resonance imaging (MRI) contrasts is time-intensive and uncomfortable for patients, despite the diagnostic value of

VIS-Ground: Video Interactive Storytelling with Contextual Grounding

arXiv:2610.09326v1 Announce Type: new Abstract: Video interactive storytelling enables viewers to actively steer how a video unfolds. However, once we allow viewers to intervene during generation, a n

What a Reporting Convention Hides: A Matched-Budget Audit of Quantum Natural Gradient with an Exactly Computed Metric

arXiv:2610.09425v1 Announce Type: new Abstract: Several published comparisons of variational quantum optimizers time only runs that reach a target loss, or read the verdict at a single target. Either

What Can a Gaussian Process Design Test

arXiv:2610.10122v1 Announce Type: new Abstract: A Gaussian process (GP) model can agree with the data for two reasons: its assumptions are right, or the chosen inputs could never have shown that they

What Makes Synthetic Hard Negatives Work in Vision-Language Pretraining?

arXiv:2610.09700v1 Announce Type: new Abstract: Synthetic hard negatives generated in the representation space have proven effective for unimodal self-supervised learning, but transferring this idea t

When Rank Rises as LLMs Degrade

arXiv:2610.09647v1 Announce Type: cross Abstract: Post-training adapts language models in non-stationary environments. Practitioners monitor representation health with RankMe and related spectral stat

When Should an In-Context Learner Expand Its Hypothesis Space?

arXiv:2610.09471v1 Announce Type: new Abstract: Learning systems adapt quickly inside a familiar family of models. The harder step comes earlier: deciding, from observations that could be noise, an ex

Which Rollout Taught It That? BehaviorTrace and the Limits of Training-Data Attribution in Online RL

arXiv:2610.10422v1 Announce Type: cross Abstract: When reinforcement learning teaches a language model a new behavior, can we find the training rollouts that taught it? And when an attribution method

Why Forget-Only Unlearning Needs Memorization

arXiv:2610.10519v1 Announce Type: new Abstract: Machine unlearning asks for a deletion algorithm whose output is close to retraining from scratch without the selected forget examples. In this work, we

WxFM-XL: Adapting Univariate Foundation Models to Multi-Station Weather Forecasting

arXiv:2610.10057v1 Announce Type: new Abstract: With the rise of univariate time series foundation models (e.g., Sundial, Timer), initial efforts have been made to extend them to multivariate settings

Your Prompt Should Do More: Effects of Retrieval Instructions in Embedding Models

arXiv:2610.10508v1 Announce Type: new Abstract: Prompted embedding models have recently received increasing attention, particularly for retrieval, where detailed retrieval instructions are provided as

Zero-Shot Brain MRI Inpainting with 2.5D Unconditional Flow Priors

arXiv:2610.08983v1 Announce Type: new Abstract: Generative inpainting of brain MRI volumes is essential for synthesizing healthy tissue in pathological regions, improving the accuracy and reliability

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 Belief-State World Model for Catheter Navigation under Sparse Fluoroscopy: A Planar Proof of Concept

arXiv:2610.08469v1 Announce Type: new Abstract: Endovascular catheter navigation relies on continuous fluoroscopy, exposing patients and clinical staff to ionizing radiation throughout the procedure.

researcharxiv-cs-ro

A BEMD-Based Quaternion Filtering Approach Sharp-to-Soft Kernel CT Image Conversion

arXiv:2610.07071v1 Announce Type: new Abstract: The quality of computed tomography (CT) images is significantly affected by the selection of reconstruction kernels: sharp kernels improve spatial resol

A Broader Look at Model Merging: Rethinking Implicit Regularization Induced by Task Arithmetic

arXiv:2610.07990v1 Announce Type: cross Abstract: Model merging aims to build a multi-task model cheaply by combining the weights of individual task-specific models. To perform well across multiple ta