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arXiv:2601.20208v2 Announce Type: replace-cross Abstract: The central challenge in robotic manipulation of deformable objects lies in aligning high-level semantic instructions with physical interactio

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Research

Training and Scaling Compute-Optimal Physiological Waveform Foundation Models

DGX agent

arXiv:2610.05649v1 Announce Type: new Abstract: We investigate the scaling laws and compute-optimal training of physiological waveform foundation models (FMs). We train Aether, a family of over one hu

researcharxiv-cs-lg

6 Oct 2026

Training-Free Transformer Merging via Sequential Local Operator Alignment

arXiv:2610.06415v1 Announce Type: new Abstract: Training-free model merging aims to combine multiple fine-tuned models into a single model without further optimization on labeled data. Yet, in transfo

Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery

arXiv:2610.03872v1 Announce Type: cross Abstract: AI agents are becoming increasingly capable of generating scientific code, but generating code is not the same as improving the algorithms behind it.

tutorialsarxiv-cs-lg

Trajectory-Derived Confidence for Reliable, Resource-Aware Clinical Text-to-SQL Agents

arXiv:2610.04156v1 Announce Type: cross Abstract: LLM agents for clinical text-to-SQL applications reason autonomously over multiple steps but cannot assess whether their own reasoning or outputs can

Trajectory-Guided Tokenization of Complex CSI for Wi-Fi Sensing

arXiv:2610.06288v1 Announce Type: new Abstract: Wi-Fi channel state information (CSI) enables contactless presence detection and gesture recognition. Its high-dimensional complex-valued time series re

Transfer-Stratified On-Policy Distillation for RL-Improved Reasoning Teachers

arXiv:2610.05974v1 Announce Type: new Abstract: Reinforcement learning can substantially improve a reasoning teacher, but it is unclear which of those improvements survive when the teacher supervises

Transferable Adversarial Robustness for Speech Foundation Models via Hierarchical Stabilization

arXiv:2610.05310v1 Announce Type: cross Abstract: Frozen speech foundation models (SFMs) make downstream adaptation efficient: the backbone can stay fixed while a task learns layer fusion and a lightw

Transform Trained Transformer for Accelerating Native 4K Video Generation

arXiv:2512.13492v2 Announce Type: replace Abstract: Native 4K (2176imes3840) video generation remains a critical challenge due to the quadratic computational explosion of full-attention as spatiotempo

Transformer Based Time-Series Forecasting for Stock

arXiv:2502.09625v2 Announce Type: replace-cross Abstract: To the naked eye, stock prices are considered chaotic, dynamic, and unpredictable. Indeed, it is one of the most difficult forecasting tasks t

Transporting Unsecured Stacked Payloads with a Quadrupedal Robot via Multi-Objective Reinforcement Learning

arXiv:2610.05819v1 Announce Type: cross Abstract: Transporting unsecured payloads with legged robots over uneven terrain requires balancing locomotion performance and payload stability, since aggressi

Agents

Traversability-Aware Cooperative Path Planning for Human-UGV Casualty Evacuation

arXiv:2610.06487v1 Announce Type: new Abstract: Heterogeneous multi-robot path planning is a well-studied problem in which agents with disparate kinematic and dynamic models must coordinate to achieve

agentsarxiv-cs-ro

TreeWalker: Partial Evaluation for Grouped Tree-Ensemble Inference

arXiv:2610.03939v1 Announce Type: new Abstract: Many inference workloads evaluate a trained tree ensemble on row groups that share feature values: discrete-time survival models expand each patient int

Triggering Generalist Reasoning via Predictive Uncertainty for Dual-System VLA

arXiv:2610.05025v1 Announce Type: new Abstract: Dual-system Vision-Language-Action (VLA) models improve real-time robotic control by pairing a slow, reasoning-capable generalist with a fast specialist

TRIM-ReID: Duplication-Aware Token Reduction and Modality-Aligned Interaction for Multi-Modal Object Re-Identification

arXiv:2610.04361v1 Announce Type: new Abstract: Multi-modal object re-identification exploits complementary RGB, near-infrared (NIR), and thermal-infrared (TIR) observations to retrieve target objects

safetyarxiv-cs-cv

Trinity: One Differentiable Physics for Training, Refining and Scoring Generative Floorplanners

arXiv:2610.04957v1 Announce Type: new Abstract: Floorplanning arranges the blocks of a chip and decides their shapes under objectives that press blocks together, short wirelength and a small outline,

Trust the View That Sees the Target: Mining Cross-View Conflicts for Reliability-Gated Disaster Damage Assessment

arXiv:2610.04327v1 Announce Type: new Abstract: After a disaster, building damage is assessed from overhead tiles and ground-level photographs, and most methods fuse the two views symmetrically, trust

Local Ai

TrustmeWatcher: An Application for Workplace Micro-Sensing and Explainable Well-Being Feedback

arXiv:2610.06657v1 Announce Type: new Abstract: Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interf

local-aiarxiv-cs-lg

TSAE: Structured Sparse Autoencoders for Interpreting Time-Series Forecasting Models

arXiv:2610.04925v1 Announce Type: new Abstract: Time-series forecasting informs critical decisions in energy dispatch, industrial operations, and environmental monitoring; understanding the patterns m

TUCO: Curating Simulation Demonstrations for Sim-to-Real Robot Policy Co-Training

arXiv:2610.05407v1 Announce Type: new Abstract: Simulation demonstrations can supplement scarce real-world data for robot policy co-training. However, the value of using data curation to actively sele

safetyarxiv-cs-ro

TurboPairFormer: Fast and Stable Protein Folding Model Training with an Optimized Triangle Attention Kernel

arXiv:2610.05854v1 Announce Type: new Abstract: Triangular attention is a core computation in AlphaFold3-style biomolecular models, with cubic cost in token count. Its shared pair bias adds a gradient

Two Americas of Well-Being: Divergent Rural-Urban Patterns of Life Satisfaction and Happiness from 2.6 B Social Media Posts

arXiv:2511.10542v2 Announce Type: replace-cross Abstract: Using 2.6 billion geolocated social-media posts (2014-2022) and a fine-tuned generative language model, we construct county-level indicators o

Two-Point Local Optimality in k-Means via Boundary-Point Screening

arXiv:2610.06182v1 Announce Type: new Abstract: Lloyd's algorithm and the discrete local (D-local) optimization method (Li et al., 2025) for k-means provide only weak local-optimality guarantees, and

Two-Sample Testing via Path-based Inference

arXiv:2610.05684v1 Announce Type: cross Abstract: Modern deep generative models are primarily studied for their ability to generate realistic samples, yet the generative dynamics they learn can also s

ufakzeka-karar: An Open Turkish Typed-Decision Model with Order-Invariant Option Scoring

arXiv:2610.06744v1 Announce Type: cross Abstract: ufakzeka-karar is an open Turkish decision model with 182,494,466 parameters. Given a Turkish text and questions of a fixed answer type (a choice, a l

UltraDub: Towards Authentic Dubbing by Unifying Visually-Steered Flow Learning and Trajectory Guidance

arXiv:2610.05932v1 Announce Type: new Abstract: Visual voice cloning requires intelligible, speaker-consistent speech synchronized with visible articulation. However, sequential multimodal conditionin

Ultrasound Operator Guidance Using World Modeling and Retrieval Based Action Planning

arXiv:2610.06008v1 Announce Type: cross Abstract: Ultrasound is widely used, but acquisition quality is heavily dependent on the operator's knowledge and expertise. With demand for examinations outpac

tutorialsarxiv-cs-cv

UnAct: Gradient-Free Unlearning via Targeted Activation Intervention

arXiv:2610.04426v1 Announce Type: cross Abstract: Machine unlearning seeks to remove the influence of designated training data from a trained model without retraining from scratch. Retrain-free method

Underscoring the Problem: Why Softpick Fails at Initialization

arXiv:2610.05488v1 Announce Type: new Abstract: Softmax attention gives every token a nonzero weight, which in trained models concentrates into attention sinks and massive activations that widen the d

Understanding Certified Training with Interval Bound Propagation

arXiv:2306.10426v3 Announce Type: replace Abstract: As robustness verification methods are becoming more precise, training certifiably robust neural networks is becoming ever more relevant. To this en

Understanding Clustering in Slot Attention via Particle Dynamics

arXiv:2610.04493v1 Announce Type: cross Abstract: Studying attention through the lens of interacting particle dynamics has shown how token clustering can emerge from the underlying dynamics. We extend

Understanding Gap-Dependent Regret for Optimism-Based Reinforcement Learning with Linear Function Approximation

arXiv:2602.20297v2 Announce Type: replace-cross Abstract: We study gap-dependent regret for reinforcement learning with linear function approximation. While prior works have established gap-dependent

Understanding over-squashing and bottlenecks on graphs via curvature

arXiv:2111.14522v4 Announce Type: replace-cross Abstract: Most graph neural networks (GNNs) use the message passing paradigm, in which node features are propagated on the input graph. Recent works poi

Understanding the Weight Averaging Mechanism in LLM Training for Post-Training Quantization

arXiv:2610.05329v1 Announce Type: new Abstract: Large language models (LLMs) are typically pretrained in high precision but increasingly deployed with low-precision post-training quantization (PTQ). R

UniBRep: Learning Unified Geometry and Topology for Image-conditioned B-Rep Generation

arXiv:2610.04092v1 Announce Type: new Abstract: Generating a boundary representation (B-rep) conditioned on a single image requires faithful reconstruction of geometry, valid topology, and support for

Uniform-in-time convergence bounds for Persistent Contrastive Divergence algorithms

arXiv:2510.01944v2 Announce Type: replace-cross Abstract: We propose a continuous-time formulation of a noisy persistent contrastive divergence (PCD)-like method for maximum likelihood estimation (MLE

Agents

UniFunc3D: Unified Active Spatial-Temporal Grounding for 3D Affordance Segmentation

arXiv:2603.23478v2 Announce Type: replace Abstract: Affordance segmentation in 3D scenes requires an agent to ground implicit natural-language instructions into precise masks of fine-grained interacti

agentsarxiv-cs-cv

UniSlider: Perceptually Uniform Sliders for Continuous Image Editing

arXiv:2610.06831v1 Announce Type: new Abstract: Sliders provide an intuitive interface for continuous image editing. In current generative approaches, however, the slider is simply a rescaling of the

Universal Test-Time Training

arXiv:2610.05484v1 Announce Type: cross Abstract: Recent Test-Time Training (TTT) architectures compress context into fast weights that are updated online and queried as memory. Existing TTT designs k

Universality and Convergence of Generative Flows

arXiv:2610.05490v1 Announce Type: new Abstract: Generative flows sample from an unnormalized target by training a flow to be balanced, and the training loss is the signal a practitioner watches. We as

Unmentioned Checklist Findings Change How Reinforcement Learning Appears to Improve Chest Radiograph Report Checking

arXiv:2610.05425v1 Announce Type: new Abstract: Automated checks of radiology reports may rely on AI-generated checklists that leave findings unmentioned. We used reinforcement learning to train a vis

Applications

Usefulness of Quantile-Aware Diffusion Modeling for Highly Imbalanced Tabular Data

arXiv:2610.05825v1 Announce Type: new Abstract: Classification problem in the context of highly imbalanced data is a major challenge in many real-world applications (e.g., FinTech, healthcare, etc.).

applicationsarxiv-cs-lg

Valid Stopping in Adaptive Generator-Verifier Loops

arXiv:2610.06432v1 Announce Type: cross Abstract: Numerous agentic workflows are based on a generator-verifier loop: a generator proposes candidates, a cheap verifier scores them, and the workflow ter

VAMPS: Visual and Motor Policies from Sampling-Based Planning

arXiv:2610.05331v1 Announce Type: cross Abstract: Learning robot policies directly on physical systems remains difficult because data collection is costly and policy exploration can be unsafe. We intr

Variance-Aware Fine-Grained Gap-Dependent Bounds for Online Reinforcement Learning

arXiv:2610.04752v1 Announce Type: cross Abstract: We study model-free online reinforcement learning (RL) for episodic tabular Markov decision processes, focusing on both gap-dependent regret and polic

Variance-Optimal Control Variates for Learning with Black-box Feedback

arXiv:2610.04766v1 Announce Type: new Abstract: Modern models increasingly learn through black-box oracles such as humans, optimization solvers, and external tools that provide feedback without exposi

tutorialsarxiv-cs-lg

Variational Quantum Attention for Molecular Graph Learning

arXiv:2610.04588v1 Announce Type: cross Abstract: Molecular property prediction is central to computational drug discovery, where graph neural networks learn to weight neighboring atomic environments

tutorialsarxiv-cs-lg

VCURF: Virtual Camera-based Uncertainty of Radiance Fields

arXiv:2610.04076v1 Announce Type: new Abstract: Radiance fields, implemented with either implicit (NeRF) or explicit (Gaussian Splatting) representations, are advancing the state of the art in novel v