Search: “models”

tutorialsharrison-chase--x

Verification is the hidden bottleneck for knowledge work agents, especially in legal AI — complex, long-horizon work is graded by rubrics with dozens of strict criteria. In new research with @LangChai

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VICR: Visual In-Context Restoration for Real-World Image Super-Resolution

DGX agent

arXiv:2606.00704v1 Announce Type: new Abstract: Real-world image super-resolution (Real-ISR) requires balancing structural fidelity to degraded observations with realistic detail synthesis. However, e

local-aiarxiv-cs-cv

2 Jun 2026

Tutorials

VMDNet: Temporal Leakage-Free Variational Mode Decomposition for Electricity Demand Forecasting

arXiv:2509.15394v3 Announce Type: replace Abstract: Accurate electricity demand forecasting is challenging due to the strong multi-periodicity of real-world demand series, which makes effective modeli

tutorialsarxiv-cs-lg

WebSpline: Structure-Informed Splines for Real-Time 3D Gaussians from Monocular Videos

arXiv:2606.02096v1 Announce Type: new Abstract: Dynamic scene reconstruction from monocular videos remains highly challenging, as existing methods often struggle to balance global structural coherence

local-aiarxiv-cs-cv

When Knowledge Is Not Free: Cost-Aware Evidence Selection in Retrieval-Augmented Generation

arXiv:2606.02245v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) typically assumes that external knowledge is free, but many high-quality sources are paywalled, licensed, restricte

agentsarxiv-cs-cl

Whole-Body Inverse Kinematics with Graph Diffusion

arXiv:2606.00086v1 Announce Type: new Abstract: Inverse kinematics (IK) is a fundamental problem in robotics, requiring the generation of joint configurations that satisfy target end-effector poses. E

researcharxiv-cs-ro

Applications

WISE: A Multimodal Search Engine for Visual Scenes, Audio, Objects, Faces, Speech, and Metadata

arXiv:2602.12819v2 Announce Type: replace-cross Abstract: In this paper, we present WISE, an open-source audiovisual search engine which integrates a range of multimodal retrieval capabilities into a

applicationsarxiv-cs-cv

Tools

@xai @imagine see more about flipbook from @zan2434 and @eddiejiao_obj ! https://x.com/eddiejiao_obj/status/2046975783324004732?s=20

@xai @imagine see more about flipbook from @zan2434 and @eddiejiao_obj ! https://x.com/eddiejiao_obj/status/2046975783324004732?s=20 What if your whole computer were just pixels streamed to you from a

toolsswyx--x

Tools

you have to give @MicrosoftAI props for training all these in-house from scratch and getting ALL of them to near-SOTA. Mustafa built a full …

you have to give @MicrosoftAI props for training all these in-house from scratch and getting ALL of them to near-SOTA. Mustafa built a full fledged neolab inside Microsoft in 2 years, that now MS full

toolsswyx--x

Hardware

A lot more to come! We are excited to work closely with NVIDIA on the Cosmos Coalition

hardwarecristobal-valenzuela--x

A lot more to come! We are excited to work closely with NVIDIA on the Cosmos Coalition Introducing the Cosmos Coalition A new global initiative with NVIDIA and leading AI labs to build and open-source

A Novel Evaluation Metric for Unsupervised Learning in AIS-Based Maritime Anomaly Detection: MADQI

arXiv:2605.30388v1 Announce Type: new Abstract: This paper introduces a new systematic framework for detecting anomalies in maritime Automatic Identification System (AIS) datasets. These anomalies inc

A Perturbation Approach to Unconstrained Linear Bandits

arXiv:2603.28201v2 Announce Type: replace Abstract: We revisit the standard perturbation-based approach of Abernethy et al. (2008) in the context of unconstrained Bandit Linear Optimization (uBLO). We

A Survey on Semantic Communication for Vision: Categories, Frameworks, Enabling Techniques, and Applications

arXiv:2601.22202v2 Announce Type: replace-cross Abstract: Semantic communication (SemCom) emerges as a transformative paradigm for traffic-intensive visual data transmission, shifting focus from raw d

researcharxiv-cs-cv

Active Timepoint Selection for Learning Measure-Valued Trajectories

arXiv:2605.30625v1 Announce Type: cross Abstract: Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data

safetyarxiv-cs-ai

Adaptive Artificial Time-Delay Control with Barrier Lyapunov Constraints for Euler-Lagrange Robots

arXiv:2605.31405v1 Announce Type: new Abstract: This paper addresses the challenge of simultaneously compensating for state-dependent uncertainties and enforcing time-varying state constraints in Eule

safetyarxiv-cs-ro

Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems

arXiv:2602.11208v2 Announce Type: replace Abstract: The Earth's subsurface is a cornerstone of modern society, providing essential energy resources like hydrocarbons, geothermal, and minerals while se

local-aiarxiv-cs-lg

AI for Monitoring and Classifying Data Used in Research Literature

arXiv:2605.30582v1 Announce Type: new Abstract: While platforms like Google Scholar and Semantic Scholar track citations for academic papers, no comparable infrastructure exists for monitoring dataset

researcharxiv-cs-cl

Annotations Are Not All You Need: A Cross-modal Knowledge Transfer Network for Unsupervised Temporal Sentence Grounding

arXiv:2605.30742v1 Announce Type: new Abstract: This paper addresses the task of temporal sentence grounding (TSG). Although many respectable works have made decent achievements in this important topi

safetyarxiv-cs-cv

Asymptotically Optimal Sequential Testing with Markovian Data

arXiv:2602.17587v2 Announce Type: replace-cross Abstract: We study one-sided and alpha-correct sequential hypothesis testing for data generated by an ergodic, finite-state Markov chain. The null hypot

Automatically Attacking Software Reverse Engineering AI Agents

arXiv:2605.30667v1 Announce Type: cross Abstract: Software tools for reverse engineering executable binary files, such as Ghidra, enable malware analysts to safely conduct robust static analysis witho

agentsarxiv-cs-ai

b9452

llama.cpp b9452 is a release of the LLM inference C/C++ project from the ggml-org repository. This release likely includes updates to the software's core functionality, bug fixes, or new features that

b9455

Release b9455 is a build of llama.cpp, a C/C++ implementation for LLM inference . This release represents a specific commit or version update to the llama.cpp project, which is used for running large

b9459

Release b9459 is a version of llama.cpp, the C/C++ implementation for LLM inference. The specific release would contain bug fixes, optimizations, or new features for the llama.cpp project, which enabl

b9464

Release b9464 is a version of llama.cpp, a project that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware. This specific release likely contains upd

Hardware

Batched Differentiable Rigid Body Dynamics in PyTorch for GPU-Accelerated Robot Learning

arXiv:2605.31481v1 Announce Type: new Abstract: As robot control shifts toward large-scale reinforcement learning with in-loop dynamics computation, the community's reliance on CPU-bound libraries suc

hardwarearxiv-cs-ro

Batched Stochastic Linear Bandits with 1-Bit Communication Constraints

arXiv:2605.30976v1 Announce Type: cross Abstract: We study stochastic linear bandits under a natural combination of batching and communication constraints: the time horizon is partitioned into batches

agentsarxiv-cs-lg

Applications

Benchmarking Single-Step Inpainting Methods for Multi-Object 3D Gaussian Splatting Scenes

arXiv:2605.30987v1 Announce Type: new Abstract: The tasks of object removal and inpainting 3D Gaussian Splatting (3DGS) scenes face challenges such as 3D consistency across camera views. In comparing

applicationsarxiv-cs-cv

Beyond Tokens: Enhancing RTL Quality Estimation via Structural Graph Learning

arXiv:2508.18730v2 Announce Type: replace Abstract: Estimating the quality of register transfer level (RTL) designs is crucial in the electronic design automation (EDA) workflow, as it enables instant

Building Generalization Into Behavior Generation Via Adaptive Compositions of Regularities

arXiv:2605.31110v1 Announce Type: new Abstract: Generalization in robotics requires prior knowledge about how the world is structured, yet this structure changes from one situation to the next. This p

safetyarxiv-cs-ro

CaptionFormer: Unified Segmentation, Tracking, and Captioning for Spatio-Temporal Objects

arXiv:2510.14904v3 Announce Type: replace-cross Abstract: Dense Video Object Captioning (DVOC) is the task of jointly detecting, tracking, and captioning object trajectories in a video, requiring the

local-aiarxiv-cs-ai

Causal Evaluation of Membership Inference Attacks

arXiv:2602.02819v3 Announce Type: replace Abstract: Membership Inference Attacks (MIAs) aim to distinguish training points (members) from unseen data (non-members), and are widely used to quantify mem

safetyarxiv-cs-lg

Certified Circuits: Stability Guarantees for Mechanistic Circuits

arXiv:2602.22968v3 Announce Type: replace Abstract: Understanding how neural networks arrive at their predictions is essential for debugging, auditing, and deployment. Mechanistic interpretability pur

researcharxiv-cs-ai

COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation

arXiv:2605.31264v1 Announce Type: new Abstract: LLM agents are increasingly expected not only to complete isolated tasks, but also to carry bounded representations of human expertise, judgment, and in

agentsarxiv-cs-ai

Conformal C2ST: Turning weak classifiers into strong two-sample tests

arXiv:2507.17026v2 Announce Type: replace-cross Abstract: The two-sample testing problem, a fundamental task in statistics and machine learning, seeks to determine whether two sets of samples, drawn f

ConsisGuard: Aligning Safety Deliberation with Policy Enforcement in LLM Guardrails

arXiv:2605.31073v1 Announce Type: new Abstract: Reasoning-based LLM guardrails improve safety moderation by generating explicit rationales before issuing final decisions. However, their rationales do

safetyarxiv-cs-cl

Detect in Any Scene: An Agentic Framework for Object Detection with Experience-Aware Reasoning

arXiv:2605.31174v1 Announce Type: new Abstract: Object detection in real-world scenarios remains challenging due to diverse image degradations and heterogeneous object distributions, which significant

safetyarxiv-cs-cv

Tutorials

Developing a Culturally Grounded, AI-Augmented UX Research Point of View (POV): An Exemplar Case Study from Telemedicine Dementia Care

arXiv:2605.31147v1 Announce Type: cross Abstract: User Experience Research (UXR) Points of View (POVs) distil complex and often fragmented research evidence into actionable perspectives that guide how

tutorialsarxiv-cs-ai

Diagnosing the Reliability of LLM-as-a-Judge via Item Response Theory

arXiv:2602.00521v2 Announce Type: replace Abstract: While LLM-as-a-Judge is widely used in automated evaluation, existing validation practices primarily operate at the level of observed outputs, offer

safetyarxiv-cs-ai

Discovering a Zeta Map Algorithm on Dyck Paths via Mechanistic Interpretability

arXiv:2605.30482v1 Announce Type: new Abstract: Machine learning is increasingly used in mathematical discovery, but in mathematics the desired output is often not a prediction itself, but an explicit

DiTTo: Scalable Order-aware All-in-One Image Restoration Agent

arXiv:2605.30915v1 Announce Type: new Abstract: Real-world images rarely suffer from a single degradation, and the order in which degradations are removed substantially affects the final restoration q

safetyarxiv-cs-cv

Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market

arXiv:2605.30363v1 Announce Type: cross Abstract: Regime shifts in financial markets reorganise the joint dynamics of asset prices and macro variables, breaking any single-regime calibration. They are

safetyarxiv-cs-ai

Extracting accent features in spoken Brazilian Portuguese without sociolinguistic labels

arXiv:2605.30457v1 Announce Type: cross Abstract: Regional accent classification in Brazilian Portuguese (pt-BR) suffers from the need for reliable labeling. While large self-supervised learning (SSL)

researcharxiv-cs-cl

Fixed Universal Transformers

arXiv:2605.31423v1 Announce Type: new Abstract: We introduce universal transformers: fixed transformers that can simulate any transformer in a given class via a suitable input embedding. Analogous to

FLOWR: Flow Matching for Structure-Aware De Novo, Interaction- and Fragment-Based Ligand Generation

arXiv:2504.10564v3 Announce Type: replace-cross Abstract: We introduce FLOWR, a novel structure-based framework for the generation and optimization of three-dimensional ligands. FLOWR integrates conti

G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition

arXiv:2603.10468v2 Announce Type: replace-cross Abstract: We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting,

local-aiarxiv-cs-ai

GETA: Generalized Encrypted Traffic Analysis

arXiv:2605.31277v1 Announce Type: cross Abstract: Traditional traffic analysis is being fundamentally challenged by the rapid adoption of encryption, tunnelling, and privacy-preserving protocols, whic

Graph Neural Networks Are Not Continuous Across Graph Resolutions

arXiv:2605.31315v1 Announce Type: new Abstract: We show that contrary to conventional wisdom in the community, graph neural networks (GNNs) are not continuous with respect to all natural modes of grap

Group Entropies and Mirror Duality: A Class of Flexible Mirror Descent Updates for Machine Learning

arXiv:2603.08651v2 Announce Type: replace Abstract: We introduce a comprehensive theoretical and algorithmic framework that bridges formal group theory and group entropies with modern machine learning