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StimFlow: Synthesizing Brain Activity from Images via Stimulus-conditioned Flow Matching

arXiv:2610.15341v1 Announce Type: new Abstract: The inherent variability of fMRI responses across trials encourages a generative view of the stimulus-to-response mapping. Prior generative encoders oft

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Structure-preserving fidelity diagnostics for partial differential equations

DGX agent

arXiv:2610.17483v1 Announce Type: new Abstract: Machine learning surrogates of partial differential equations (PDEs) are commonly trained on data generated by numerical solvers. Therefore, the trainin

researcharxiv-cs-lg

14 Oct 2026

StructZO: Structured Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning

arXiv:2610.16451v1 Announce Type: new Abstract: Fine-tuning large language models at scale is increasingly limited by the memory cost of backpropagation. Zeroth-Order (ZO) optimizers reduce this burde

Surface Reconstruction from Range Scans Under Visibility Constraints

arXiv:2610.18005v1 Announce Type: new Abstract: Surface reconstruction from range scans is challenging in the presence of noise and outliers, as fidelity to observations must be balanced against sensi

SurgCast: Action-Conditioned Future Skeletons for Controllable Surgical World Models

arXiv:2610.15645v1 Announce Type: new Abstract: Surgical world models must turn prospective robot actions into visually faithful, structurally consistent instrument motion. We introduce SurgCast, whic

SWORD: Scene-Grounded Wasserstein Object-Relation Distance for 3D Scene Graph Prediction

arXiv:2610.17692v1 Announce Type: new Abstract: 3D scene graph prediction is commonly optimized with object-node and relation-edge classification losses. These objectives encourage exact object and re

TabGift: A Context-Efficient Foundation Model for Tabular Data Generation

arXiv:2610.16990v1 Announce Type: new Abstract: Tabular data generation aims to synthesize realistic samples from limited observations while faithfully capturing the underlying data distribution. Tabu

TableVision: Recovering Verified Structure from Historical Tables

arXiv:2610.17448v1 Announce Type: new Abstract: Gaps, skips, and mistakes are the normal state of a historical register: rows go missing, tables cross page breaks, columns slip under wrong names, and

TAG: Calibrating SAM3 for Universal Image Segmentation without Dense Supervision

arXiv:2610.14651v1 Announce Type: new Abstract: The recent Segment Anything Model 3 (SAM3) extends powerful promptable segmentation from spatial cues to concepts, raising the prospect of a single foun

TagBO: LLM-Driven Task-Aware Graph Bayesian Optimization for Scientific Discovery

arXiv:2610.14626v1 Announce Type: new Abstract: Mixed-variable optimization in scientific discovery often requires exploring large combinatorial spaces under costly experimental evaluations, making sa

Taming Nonconvexity with Epigraph Lifting

arXiv:2610.16429v1 Announce Type: cross Abstract: We consider inverse problems regularized by a trained neural network with convex activations and unrestricted weights. The resulting optimization prob

Task-Space Motion-Force Nonlinear Model Predictive Control for Precise and Compliant Control under Uncertainties

arXiv:2610.17069v1 Announce Type: new Abstract: In Nonlinear Model Predictive Control (NMPC), the control law is implicitly determined by the solution of an Optimal Control Problem (OCP). Consequently

researcharxiv-cs-ro

Teaching MLP More Graph Information: A Three-stage Multitask Knowledge Distillation Framework

arXiv:2403.01079v2 Announce Type: replace Abstract: We study the challenging problem for inference tasks on large-scale graph datasets of Graph Neural Networks: huge time and memory consumption, and t

Teaching Vision-Language Models to Decline: Support Completion Against Mirage

arXiv:2610.16465v1 Announce Type: new Abstract: Vision-language models answer questions about images they were never shown, a failure called mirage. Such an answer can be correct without being justifi

Temporal Diffusion Bridge Model for Vessel Extraction Using Physics-informed Synthetic Data

arXiv:2610.14105v1 Announce Type: cross Abstract: Accurate artery extraction from X-ray coronary angiography (XCA) is essential for coronary artery disease diagnosis and intervention. However, low ves

Tensor-reduced atomic density representations

arXiv:2210.01705v3 Announce Type: replace-cross Abstract: Density based representations of atomic environments that are invariant under Euclidean symmetries have become a widely used tool in the machi

Test-Time Compute for Humanoid Behavior Foundation Models

arXiv:2610.14896v1 Announce Type: new Abstract: Humanoid Behavior Foundation Models (BFMs) can execute impressive motions, but downstream applications such as loco-manipulation demand high whole-body

researcharxiv-cs-ro

Testing Central Structure for Complex Networks

arXiv:2610.15659v1 Announce Type: new Abstract: Centrality measures rank nodes even when the observed differences can be explained by ordinary structural variation. We therefore study a preceding ques

TETRIS-4DGS: Efficient Post-Training Compression of 4D Gaussian Splatting

arXiv:2610.14663v1 Announce Type: new Abstract: 4D Gaussian Splatting (4DGS) has emerged as a powerful dynamic scene representation, supporting real-time high quality rendering but suffers from prohib

Text-Only vs. Image-Aware VLM Judges for Manga Translation Evaluation

arXiv:2610.17908v1 Announce Type: cross Abstract: In manga translation, visual context outside speech-bubble text, including speaker identities, referents, and scene tone, is depicted in page images,

textGrain watermarking is harder to detect: can sum-tests still do it optimally?

arXiv:2610.17655v1 Announce Type: cross Abstract: Watermarking embeds an imperceptible signal in text from large language models that is statistically detectable with a secret key. The recent textGrai

TGSR: Text-Grounded Diffusion for Faithful Image Super-Resolution

arXiv:2610.14281v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in image super-resolution (SR) by leveraging strong generative priors to enhance perceptual quality. H

TGuide: Faster Autoregressive Video Diffusion via Historical Trajectory Guidance

arXiv:2610.14657v1 Announce Type: new Abstract: Can autoregressive video diffusion be accelerated further when only four denoising steps remain? Existing feature caching approaches struggle in this re

The belief-action gap in language model agents

arXiv:2610.17444v1 Announce Type: new Abstract: Language model (LM) agents can fail for different reasons, requiring different explanations and interventions. We study how state beliefs, action values

The Bell Boundary of Shared Representations

arXiv:2610.16828v1 Announce Type: new Abstract: When does a shared representation become insufficient for jointly supporting multiple tasks? This question lies at the heart of multi-task learning mode

The Design Space of Tri-Modal Masked Diffusion Models

researchapple-ml-research

Discrete diffusion models have emerged as strong alternatives to autoregressive language models, with recent work initializing and finetuning a base unimodal model for bi-modal generation. Diverging f

The Effect of Layer Ordering in Hybrid Architectures

arXiv:2610.18104v1 Announce Type: new Abstract: Hybrid attention is rapidly becoming the dominant architectural choice for frontier models. Despite their successes, such architectures complicate model

The Geometry of the Set of Equivalent Linear Neural Networks

arXiv:2404.14855v2 Announce Type: replace Abstract: We characterize the geometry of the set of all weight vectors for which a fully-connected linear neural network computes the same linear transformat

The Language of Looking: Motion Tokens Reveal Domain-Dependent Local Structure in Gaze Sequences

arXiv:2610.16565v1 Announce Type: new Abstract: Human gaze is the primary high-bandwidth interface through which we parse the semantics of our environment. While often modeled as a sequence, the degre

The Midas Touch for Metric Depth: Interpretable Metricization for Generalizable Depth Perception

arXiv:2610.16749v1 Announce Type: new Abstract: Recent foundation models have drastically improved the generalization of monocular relative depth estimation, yet recovering accurate metric depth from

The Optimal Decoder is Tilted Temperature

arXiv:2610.15058v1 Announce Type: new Abstract: Larger sample budgets benefit from higher sampling temperatures in LLMs, but what temperature tuning optimizes and why it works remain poorly understood

The Surprising Expressivity of a Single Neuron with Autoregressive Chain-of-Thought

arXiv:2610.17283v1 Announce Type: new Abstract: The success of autoregressive language models trained with Chain-of-Thought~(CoT) supervision raises a fundamental question: How simple can a next-token

The Value of Being Wrong: Self-Mined Visual In-Context Learning from Errors

arXiv:2610.16977v1 Announce Type: new Abstract: Visual in-context learning (ICL) enables vision-language models (VLMs) to adapt at test time via demonstration examples, but its effectiveness depends c

Thinking with Images without Coordinates

arXiv:2610.14265v1 Announce Type: new Abstract: Recent advances in multi-modal large language models have shifted toward the 'thinking with images' paradigm to improve reasoning faithfulness, yet exis

TIDE: Trajectory-Informed Skill Distillation for Efficient Text-to-Video Prompt Optimization

arXiv:2610.15098v1 Announce Type: new Abstract: Text-to-video (T2V) models are highly sensitive to prompt specificity, while iterative prompt optimization typically improves generation quality only th

Tight End-to-End Accounting for Differentially Private Synthetic Data

arXiv:2610.17249v1 Announce Type: cross Abstract: Differentially private (DP) pipelines often combine heterogeneous mechanisms, yet their guarantees are best analyzed using different notions of privac

ToF-Wheel Odometry: Navigating Degeneration of Localization With Limited Sensing Capabilities

arXiv:2610.14590v1 Announce Type: cross Abstract: Wheel odometry provides an efficient motion prior for ground robots but is prone to transient violations such as wheel slip or terrain-induced tilt. I

Token-Budgeted Candidate Retrieval for 3D Scene-Grounded VLMs: Category Names vs. Pairwise Geometry

arXiv:2610.14207v1 Announce Type: new Abstract: Under a fixed context budget, which objects and relations should a 3D scene-grounded VLM see first? On ScanNet indoor referring benchmarks (Dai et al.,

Totem: Object-Centric 3D Memory for World-Consistent Video Generation

arXiv:2610.15807v1 Announce Type: new Abstract: Generating coherent videos grounded in a unified underlying world remains a major challenge, particularly under large viewpoint changes, where existing

Toward Guarantees for Clinical Reasoning in Vision Language Models via Formal Verification

arXiv:2602.24111v2 Announce Type: replace Abstract: Vision-language models (VLMs) show promise in drafting radiology reports, yet they frequently suffer from logical inconsistencies, generating diagno

Toward Study on the Effects of Robot's Humorous Apology on Human's Trust Recovery

arXiv:2610.16334v1 Announce Type: new Abstract: Robot errors can disrupt human-robot collaboration by reducing user trust and willingness to rely on the robot. Robot apologies can support trust recove

researcharxiv-cs-ro

Towards Complementary Keypoint Detection via Mixture of Detectors

arXiv:2610.16762v1 Announce Type: new Abstract: Keypoint detection plays a central role in geometric vision pipelines. Existing detectors exhibit complementary strengths across different scene structu

Towards Cost-Efficient Video Dataset Construction with Large Language Models

arXiv:2610.16857v1 Announce Type: new Abstract: Research on video classification models has witnessed significant growth recently, accompanied by a significant increase in the demand for datasets to t

TRACE: Temporal Risk Assessment and Concept Editing for Safer Language Generation

arXiv:2610.15365v1 Announce Type: cross Abstract: Large language models (LLMs) can produce harmful content while generating a response. A useful safeguard should not only detect this risk during gener

TraceSampler: Making Sampling Errors Predictable and Correctable for Accelerated Generative Sampling

arXiv:2610.14332v1 Announce Type: new Abstract: Accurate sampling from continuous-time generative models can require many model evaluations. Low-step sampling reduces cost, but coarse updates introduc

Traditional and Recent Approaches for Infrared Small Target Detection : Overview, Challenges and Perspectives (Part 1)

arXiv:2610.18276v1 Announce Type: new Abstract: Infrared small target detection is often used in different civilian and military applications to detect static or moving targets in scenes like in groun

Train for Many, Update with One: Improving Multi-Sample Reasoning via Fenchel-Bregman Posterior Learning

arXiv:2610.17735v1 Announce Type: new Abstract: Multi-sample reasoning measures candidate coverage, the probability that at least one of K candidates is correct. However, minimizing the average loss o

Training-Free Dense Hand Contact Estimation with Multi-Modal Large Language Models

arXiv:2605.05886v2 Announce Type: replace Abstract: Dense hand contact estimation requires both high-level semantic understanding and fine-grained geometric reasoning of human interaction to accuratel