All entries

Statistical inference with belief functions: A survey

arXiv:2605.07908v1 Announce Type: cross Abstract: Belief functions are a powerful and popular framework for the mathematical characterisation of uncertainty, in particular in situations in which lack

tutorialsarxiv-cs-ai

Statistical Patterns in the Equations of Physics and the Emergence of a Meta-Law of Nature

DGX agent

arXiv:2408.11065v2 Announce Type: replace-cross Abstract: Physics seeks to uncover the laws of Nature and express them through mathematical equations. Despite the vast diversity of natural phenomena,

researcharxiv-cs-cl

11 May 2026

STDA-Net: Spectrogram-Based Domain Adaptation for cross-dataset Sleep Stage Classification

arXiv:2605.06736v1 Announce Type: cross Abstract: Accurate sleep stage classification across datasets remains challenging due to variability in EEG channel montages, sampling rates, recording environm

SteelDefectX: A Multi-Form Vision-Language Dataset and Benchmark for Steel Surface Defect Analysis

arXiv:2603.21824v2 Announce Type: replace-cross Abstract: Steel surface defect analysis is critical for industrial quality control, yet existing benchmarks rely primarily on label-only annotations, li

STEPS: A Temporal Smooth Error Propagation Solver on the Manifolds for Test-Time Adaptation in Time Series Forecasting

arXiv:2605.08005v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) aims to improve time series forecasting under distribution shifts by using limited observations revealed during inference. Ho

Stochastic Transition-Map Distillation for Fast Probabilistic Inference

arXiv:2605.07661v1 Announce Type: cross Abstract: Diffusion models achieve strong generation quality, diversity, and distribution coverage, but their performance often comes with expensive inference.

Streaming Adversarial Robustness in Fuzzy ARTMAP: Mechanism-Aligned Evaluation, Progressive Training, and Interpretable Diagnostics

arXiv:2605.06902v1 Announce Type: new Abstract: Adversarial robustness has been studied extensively for offline deep networks, but less is known about strict single-pass streaming neural learners. Thi

StreamPhy: Streaming Inference of High-Dimensional Physical Dynamics via State Space Models

arXiv:2605.07384v1 Announce Type: new Abstract: Inferring the evolution of high-dimensional and multi-modal (e.g., spatio-temporal) physical fields from irregular sparse measurements in real time is a

Structural Rationale Distillation via Reasoning Space Compression

arXiv:2605.07139v1 Announce Type: cross Abstract: When distilling reasoning from large language models (LLMs) into smaller ones, teacher rationales for similar problems often vary wildly in structure

researcharxiv-cs-ai

Structure learning of Hamiltonians from real-time evolution

arXiv:2405.00082v4 Announce Type: replace-cross Abstract: We study the problem of Hamiltonian structure learning from real-time evolution: given the ability to apply e^{-i Ht} for an unknown local Ham

tutorialsarxiv-cs-lg

Structure Over Scale: Learning Visual Reasoning from Pedagogical Video

model-releasesarxiv-cs-cv

arXiv:2601.23251v2 Announce Type: replace Abstract: State-of-the-art vision-language models (VLMs) score impressively on video benchmarks yet stumble on basic visual reasoning tasks involving spatial

Structured Coupling for Flow Matching

arXiv:2605.07676v1 Announce Type: new Abstract: Standard flow matching scales well but typically relies on an unstructured source distribution, limiting its ability to learn interpretable latent struc

tutorialsarxiv-cs-lg

Structured Prototype-Guided Adaptation for EEG Foundation Models

model-releasesarxiv-cs-lg

arXiv:2602.17251v2 Announce Type: replace Abstract: Electroencephalography (EEG) foundation models (EFMs) have shown strong potential for transferable representation learning, yet their adaptation in

Structured Role-Aware Policy Optimization for Multimodal Reasoning

arXiv:2605.07274v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR), especially with Group Relative Policy Optimization (GRPO), has shown strong potential for improvi

Industry

Such hypocrisy

Such hypocrisy Same move. Same hand on the heart, same wave to the crowd. Musk did it and gets called a Nazi to this day. Mamdani does it and those same people have not said a word. Well, not exactly.

industryelon-musk--x

Supervised sparse auto-encoders for interpretable and compositional representations

arXiv:2602.00924v2 Announce Type: replace Abstract: Sparse auto-encoders (SAEs) have re-emerged as a prominent method for mechanistic interpretability, yet they face two significant challenges: the no

Surgical Visual Understanding (SurgVU) Dataset

arXiv:2501.09209v2 Announce Type: replace Abstract: Owing to recent advances in machine learning and the ability to harvest large amounts of data during robotic-assisted surgeries, surgical data scien

Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning

arXiv:2605.07980v1 Announce Type: new Abstract: These notes introduce the theory of susceptibilities as developed in [arXiv:2504.18274, arXiv:2601.12703] for interpreting neural networks. The suscepti

local-aiarxiv-cs-lg

Swap models & view their capabilities! Try out in Deep Agents CLI: https://docs.langchain.com/oss/python/deepagents/cli/

model-releasesharrison-chase--x

Swap models & view their capabilities! Try out in Deep Agents CLI: https://docs.langchain.com/oss/python/deepagents/cli/ here's model profile details look like in practice, using @NVIDIAAIDev's Nemotr

SWaRL: Safeguard Code Watermarking via Reinforcement Learning

arXiv:2601.02602v2 Announce Type: replace-cross Abstract: We present SWaRL, a robust and fidelity-preserving watermarking framework designed to protect the intellectual property of code LLMs by embedd

Agents

Switchcraft: AI Model Router for Agentic Tool Calling

arXiv:2605.07112v1 Announce Type: new Abstract: Agentic AI systems that invoke external tools are powerful but costly, leading developers to default to large models and overspend inference budgets. Mo

agentsarxiv-cs-ai

Applications

Switching-time bioprocess control with pulse-width-modulated optogenetics

arXiv:2511.22893v2 Announce Type: replace-cross Abstract: Biotechnology can benefit from dynamic control to improve production efficiency. In this context, optogenetics enables modulation of gene expr

applicationsarxiv-cs-ai

Sword: Style-Robust World Models as Simulators via Dynamic Latent Bootstrapping for VLA Policy Post-Training

arXiv:2605.07288v1 Announce Type: cross Abstract: The integration of Vision-Language-Action (VLA) models with World Models has gained increasing attention. One representative approach treats learned W

Applications

Sycophantic AI makes human interaction feel more effortful and less satisfying over time

arXiv:2605.07912v1 Announce Type: cross Abstract: Millions of people now turn to artificial intelligence (AI) systems for personal advice, guidance, and support. Such systems can be sycophantic, frequ

applicationsarxiv-cs-ai

Synergistic Benefits of Joint Molecule Generation and Property Prediction

arXiv:2504.16559v3 Announce Type: replace Abstract: Modeling the joint distribution of data samples and their properties allows to construct a single model for both data generation and property predic

SynthForensics: Benchmarking and Evaluating People-Centric Synthetic Video Deepfakes

model-releasesarxiv-cs-cv

arXiv:2602.04939v2 Announce Type: replace Abstract: Modern T2V/I2V generators synthesize people increasingly hard to distinguish from authentic footage, while current evaluation suites lag: legacy ben

Tables Guide Vision: Learning to See the Heart through Tabular Data

arXiv:2503.14998v3 Announce Type: replace Abstract: Contrastive learning methods in computer vision typically rely on augmented views of the same image or multimodal pretraining strategies that align

tutorialsarxiv-cs-cv

Applications

Tacit Knowledge Extraction via Logic Augmented Generation and Active Inference

arXiv:2605.07639v1 Announce Type: new Abstract: Tacit knowledge plays a central role in human expertise, yet it remains difficult to capture, formalize, and reuse in machine-interpretable form. This c

applicationsarxiv-cs-ai

TAG-K: Tail-Averaged Greedy Kaczmarz for Computationally Efficient and Performant Online Inertial Parameter Estimation

model-releasesarxiv-cs-ro

arXiv:2510.04839v2 Announce Type: replace Abstract: Accurate online inertial parameter estimation is essential for adaptive robotic control, enabling real-time adjustment to payload changes, environme

TajPersLexon: A Tajik-Persian Lexical Resource and Hybrid Model for Cross-Script Low-Resource NLP

model-releasesarxiv-cs-cl

arXiv:2605.06886v1 Announce Type: new Abstract: This work introduces TajPersLexon, a curated Tajik--Persian parallel lexical resource of 40,112 word and short-phrase pairs for cross-script lexical ret

TAP: Two-Stage Adaptive Personalization of Multi-Task and Multi-Modal Foundation Models in Federated Learning

arXiv:2509.26524v3 Announce Type: replace-cross Abstract: In federated learning (FL), local personalization of models has received significant attention, yet personalized fine-tuning of foundation mod

local-aiarxiv-cs-ai

Target-Aware Data Augmentation for SAT Prediction

model-releasesarxiv-cs-lg

arXiv:2605.06931v1 Announce Type: new Abstract: Learning-based approaches to NP-hard problems have shown increasing promise, but their progress is fundamentally constrained by the high cost of generat

TAS-LoRA: Transformer Architecture Search with Mixture-of-LoRA Experts

model-releasesarxiv-cs-cv

arXiv:2605.07256v1 Announce Type: new Abstract: Transformer architecture search (TAS) discovers optimal vision transformer (ViT) architectures automatically, reducing human effort to manually design V

Task-Oriented Communication for Human Action Understanding via Edge-Cloud Co-Inference

arXiv:2605.07354v1 Announce Type: cross Abstract: The expanding application of smart sensing has created a growing demand for the accurate understanding of human action at the network edge. Traditiona

Task Relevance Is Not Local Replaceability: A Two-Axis View of Channel Information

arXiv:2605.07086v1 Announce Type: new Abstract: Channel importance in vision networks is usually summarized by a single score. That summary hides two different questions: how much a channel is related

tutorialsarxiv-cs-cv

TAVIS: A Benchmark for Egocentric Active Vision and Anticipatory Gaze in Imitation Learning

arXiv:2605.07943v1 Announce Type: cross Abstract: Active vision -- where a policy controls its own gaze during manipulation -- has emerged as a key capability for imitation learning, with multiple ind

TCMIIES: A Browser-Based LLM-Powered Intelligent Information Extraction System for Academic Literature

arXiv:2605.07507v1 Announce Type: new Abstract: The exponential growth of academic publications has created an urgent need for automated tools capable of extracting structured knowledge from unstructu

local-aiarxiv-cs-cl

TEA-Bench: A Systematic Benchmarking of Tool-enhanced Emotional Support Dialogue Agent

arXiv:2601.18700v2 Announce Type: replace Abstract: Emotional Support Conversation requires not only affective expression but also grounded instrumental support to provide trustworthy guidance. Howeve

Teacher-Feature Drifting: One-Step Diffusion Distillation with Pretrained Diffusion Representations

arXiv:2605.07327v1 Announce Type: new Abstract: Sampling from pretrained diffusion and flow-matching models typically requires many forward passes to generate diverse and high-fidelity images. Existin

Teaching Language Models to Think in Code

model-releasesarxiv-cs-cl

arXiv:2605.07237v1 Announce Type: new Abstract: Tool-integrated reasoning (TIR) has emerged as a dominant paradigm for mathematical problem solving in language models, combining natural language (NL)

Teaching Prompts to Coordinate: Hierarchical Layer-Grouped Prompt Tuning for Continual Learning

arXiv:2511.12090v3 Announce Type: replace Abstract: Prompt-based continual learning methods fine-tune only a small set of additional learnable parameters while keeping the pre-trained model's paramete

local-aiarxiv-cs-cv

TeamBench: Evaluating Agent Coordination under Enforced Role Separation

arXiv:2605.07073v1 Announce Type: new Abstract: Agent systems often decompose a task across multiple roles, but these roles are typically specified by prompts rather than enforced by access controls.

Temporal Attention for Adaptive Control of Euler-Lagrange Systems with Unobservable Memory

arXiv:2605.06877v1 Announce Type: new Abstract: Adaptive control of Euler-Lagrange systems is challenging when friction is governed by a finite-horizon internal state that is not directly observable f

safetyarxiv-cs-lg

Temporal Smoothness Doubly Robust Learning for Debiased Knowledge Tracing

arXiv:2605.05958v2 Announce Type: replace Abstract: Knowledge Tracing (KT) is fundamental to intelligent education systems, yet relies on educational logs that are selectively observed. The non-random

Tessellations of Semi-Discrete Flow Matching

arXiv:2605.07513v1 Announce Type: new Abstract: We study Flow Matching in a semi-discrete setting where a Gaussian source is transported toward a discrete target supported on finitely many points. Thi

Test-Time Compositional Generalization in Diffusion Models via Concept Discovery

arXiv:2605.07078v1 Announce Type: new Abstract: Compositional generalization requires models to produce novel configurations from familiar parts. In diffusion models, prior compositional generation me

local-aiarxiv-cs-lg

Test-Time Compute Games

arXiv:2601.21839v2 Announce Type: replace-cross Abstract: Test-time compute has emerged as a promising strategy to enhance the reasoning abilities of large language models (LLMs). However, this strate

Testing Noise Assumptions of Learning Algorithms

arXiv:2501.09189v3 Announce Type: replace Abstract: We pose a fundamental question in computational learning theory: can we efficiently test whether a training set satisfies the assumptions of a given