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FacePlex: Full-Duplex Joint Speech-Facial Motion Generation for Conversational Avatars

arXiv:2606.30145v1 Announce Type: new Abstract: Natural face-to-face conversation requires real-time speech generation together with synchronized facial motion. Existing systems only partially address

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Model Releases

Factorizable Normalizing Flows for parameter-dependent density morphing

DGX agent

arXiv:2606.30489v1 Announce Type: cross Abstract: Normalizing Flows excel at modeling a single fixed density, yet many problems across the sciences, such as high energy physics, instead require modeli

model-releasesarxiv-cs-lg

30 Jun 2026

FADA: Few-Shot Domain Adaptation via Dynamics Alignment for Humanoid Control

arXiv:2606.28476v1 Announce Type: new Abstract: High-precision humanoid control is limited by target-domain dynamics mismatch, where the same control objective can induce different realized motions un

safetyarxiv-cs-ro

FADE: Mitigating Hallucinations by Reducing Language-Prior Dominance in Large Vision-Language Models

arXiv:2606.29431v1 Announce Type: new Abstract: Despite the impressive capabilities of Large Vision-Language Models (LVLMs), they remain susceptible to hallucination, generating content inconsistent w

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation

arXiv:2602.12155v2 Announce Type: replace Abstract: Post-training of flow matching models-aligning the output distribution with a high-quality target-is mathematically equivalent to imitation learning

safetyarxiv-cs-cv

Fairness Attacks on Recommender Systems

arXiv:2606.29064v1 Announce Type: cross Abstract: The unfairness of recommender systems has become a topic of concern due to its significant social and ethical implications. Although existing works ha

safetyarxiv-cs-ai

FalconTrack: Photorealistic Auto-Labeled Perception and Physics-Aware Vision-Based Aerial Tracking

arXiv:2606.29783v1 Announce Type: cross Abstract: Vision-based aerial tracking is critical in GPS-denied environments. Reliable perception for tracking depends on large-scale labeled data, yet most ph

Falsifying Discriminant Validity of Predictive Algorithms

arXiv:2601.17146v2 Announce Type: replace-cross Abstract: Empirical investigations into unintended model behavior often show that the algorithm is predicting another outcome than what was intended. Th

Fast and Accurate Outlier-Aware LiDAR Super-Resolution for SLAM Applications

arXiv:2606.28607v1 Announce Type: cross Abstract: This work tackles the challenge of enhancing low-resolution LiDAR sensors for SLAM applications through a novel Deep Unrolling-based Super-Resolution

Fast Enough to Act: Spatio-Temporal Visual Token Merging for Low-Latency Robotic VLMs and VLAs

arXiv:2606.29350v1 Announce Type: cross Abstract: Vision-language models and vision-language action models endow the robot with unprecedented capabilities. However, the input of video and high-resolut

safetyarxiv-cs-ai

Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting

arXiv:2507.06764v5 Announce Type: replace-cross Abstract: In this work, we propose Fast Equivariant Imaging (FEI), a novel unsupervised learning framework to rapidly and efficiently train deep imaging

researcharxiv-cs-cv

Fast Numbers, Slow Language: Bridging Quantitative and Qualitative Earnings Signals

arXiv:2606.29734v1 Announce Type: new Abstract: Earnings announcements release two types of information sequentially: quantitative surprise (numeric earnings-per-share (EPS)/revenue versus analyst est

researcharxiv-cs-cl

Fast Wireless Foundation Models with Early-Exits

arXiv:2606.29640v1 Announce Type: cross Abstract: While wireless foundation models (FMs) are demonstrating strong potential to enable AI-Native 6G networks, their high computational cost remains a cri

FastPano3D: Feed-Forward Indoor Panoramic 3D Reconstruction from a Single Image

model-releasesarxiv-cs-cv

arXiv:2606.30352v1 Announce Type: new Abstract: Recent advances in 3D scene reconstruction have highlighted the intricate trade-offs among rendering quality, inference efficiency, and data dependency.

Tutorials

Faults in Our Formal Benchmarking: Dataset Defects and Evaluation Failures in Lean Theorem Proving

arXiv:2606.29493v1 Announce Type: new Abstract: Benchmarks for LLM-assisted theorem proving in Lean are often treated as intrinsically reliable because every solved instance comes with a machine-check

tutorialsarxiv-cs-ai

Favorability of Loss Landscape with Weight Decay Requires Both Large Overparametrization and Initialization

arXiv:2505.22578v2 Announce Type: replace Abstract: The optimization of neural networks under weight decay remains poorly understood from a theoretical standpoint. While weight decay is standard pract

FD^2: A Dedicated Framework for Fine-Grained Dataset Distillation

arXiv:2603.25144v2 Announce Type: replace-cross Abstract: Dataset distillation (DD) compresses a large training set into a small synthetic set, reducing storage and training cost, and has shown strong

FDM-MFVT: Few-step Sampling Diffusion Model for Mask-Free Virtual Try-On

arXiv:2606.29319v1 Announce Type: new Abstract: Image-based Virtual Try-On (IVTON) has greatly advanced through diffusion models, yet existing methods require many sampling steps and depend on masks w

safetyarxiv-cs-cv

Feature-level Interaction Explanations in Multimodal Transformers

arXiv:2603.13326v2 Announce Type: replace-cross Abstract: Multimodal Transformers often produce predictions without clarifying how different modalities jointly support a decision. Most existing multim

Tools

Featuring Every Eval Ever Results on Hugging Face Model Pages

Hugging Face introduced a feature that displays evaluation results from the 'Every Eval Ever' (EEE) community evaluation initiative directly on model pages, providing users with comprehensive benchmar

toolshugging-face

Hardware

Featuring the man of the moment @dylan522p @shaunmmaguire in today's Training Data episode. Nobody is a more trusted industry insider to the…

Featuring the man of the moment @dylan522p @shaunmmaguire in today's Training Data episode. Nobody is a more trusted industry insider to the biggest infrastructure build-out in history. The story of h

hardwaresonya-huang--x

Federated Graph Learning for EV Charging Demand Forecasting with Personalization Against Cyberattacks

arXiv:2405.00742v2 Announce Type: replace-cross Abstract: Mitigating cybersecurity risk in electric vehicle (EV) charging demand forecasting plays a crucial role in the safe operation of collective EV

Federated Learning with Energy-Based Structured Probabilistic Inference

arXiv:2606.30161v1 Announce Type: cross Abstract: Federated learning typically aggregates client updates using fixed or heuristic weighting rules, which can be suboptimal when clients have heterogeneo

FedLAS: Feature-Modulated Bidirectional Label Smoothing for Neural Network Calibration

arXiv:2606.28654v1 Announce Type: cross Abstract: Deep Neural Network (DNN) classifiers suffer from poor calibration when their softmax outputs (predictive confidence) deviate from the empirical likel

fev-bench: A Realistic Benchmark for Time Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2509.26468v3 Announce Type: replace Abstract: Benchmark quality is critical for meaningful evaluation and sustained progress in time series forecasting, particularly with the rise of pretrained

Local Ai

Few-class Fidelity: Evaluating Explanations of Real-conditions CNN classifiers with Optimized Perturbations

arXiv:2606.28391v1 Announce Type: cross Abstract: The wide use of Convolutional Neural Networks (CNN) in numerous domains and real-world classification applications is justified by their high precisio

local-aiarxiv-cs-ai

Few-Shot Domain Incremental Learning via Continual Vision-Language Consolidation

arXiv:2606.30190v1 Announce Type: cross Abstract: Existing domain-incremental learning (DIL) strategies call for massive amounts of data to adapt to new domains and suffer from the overfitting problem

Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps

arXiv:2606.29110v1 Announce Type: new Abstract: Recent progress in flow-based generative modeling has led to models that output high-quality samples while using only a small number of function evaluat

FFAvatar: Feed-Forward 4D Head Avatar Reconstruction from Sparse Portrait Images

arXiv:2606.30347v1 Announce Type: cross Abstract: We present FFAvatar, a Transformer-based 3D Gaussian framework for fast construction of high-quality and animatable 4D head avatars from one or more r

Field Order Should Not Matter: Permutation-Invariant Embedding Model Fine-Tuning for Structured Metadata Retrieval

arXiv:2606.30473v1 Announce Type: cross Abstract: We study retrieval over catalogs of structured metadata, where each record is a small schema whose fields answer different kinds of query. Embedding a

Industry

Filing: President Trump reports 1.4B+ in income from his family's crypto ventures in 2025, including 500M+ from WLF and 635M from the sale of his TRUMP coin (Reuters)

Reuters: Filing: President Trump reports 1.4B+ in income from his family's crypto ventures in 2025, including 500M+ from WLF and 635M from the sale of his TRUMP coin — U.S. President Donald Trump repo

industrytechmeme

Industry

Filings: Microsoft's Ireland hub generated $47B in pretax profits for FY 2025, or 38.1% of its global total; new EU rules require country-by-country reporting (Wall Street Journal)

Wall Street Journal: Filings: Microsoft's Ireland hub generated $47B in pretax profits for FY 2025, or 38.1% of its global total; new EU rules require country-by-country reporting — Country-by-country

industrytechmeme

Applications

Financing Artificial Intelligence Infrastructure: Mapping AI Infrastructure Investment and Compute Governance Across Africa

arXiv:2606.28404v1 Announce Type: cross Abstract: Artificial intelligence depends on large-scale compute resources and their supporting infrastructure. However, AI governance debates treat compute pri

applicationsarxiv-cs-ai

Tutorials

Fine-tune Amazon Nova models for accurate email data extraction

In this post, you'll learn how fine-tuning Amazon Nova models using Amazon SageMaker AI addresses these specific issues by teaching the models to recognize your exact data patterns, distinguish betwee

tutorialsaws-ml-blog

Fine-Tuning General-Purpose Large Language Models for Agricultural Applications:A Reproducible Framework and Evaluation Protocol Based on Qwen3-8B

arXiv:2606.28992v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) have demonstrated strong abilities in opendomain question answering, information extraction, and text gen

FinInvest-GTCN: Explainable Graph-Temporal-Causal Modeling for Risk-Aware Investment Decision Optimization

arXiv:2606.28933v1 Announce Type: new Abstract: Venture capital (VC) investment decisions face distinct challenges, such as multi-source heterogeneous data, non-stationary time series, and the demand

researcharxiv-cs-cl

FiRe: Frequency Reparameterization as a Preconditioner for Periodic Implicit Neural Representations

model-releasesarxiv-cs-cv

arXiv:2606.29414v1 Announce Type: new Abstract: Periodic Implicit Neural Representations (INRs) such as SIREN and FINER assign every neuron, the same global frequency, spending the representational bu

First-Order Temporal Logic Tensor Networks

arXiv:2606.29972v1 Announce Type: new Abstract: Most of the existing neuro-symbolic AI methods focus on the scenario of static knowledge where objects do not change according to a temporal dimension.

Fisher-Routed Mixture of Experts for Federated Class-Incremental Learning

arXiv:2606.28835v1 Announce Type: cross Abstract: Federated Learning (FL) emerged as a promising distributed machine learning paradigm. However, extending FL to the class incremental learning scenario

Applications

Five Chinese tech and advanced manufacturing companies launched Hong Kong listings today to raise up to 5.6B, led by Apple supplier Luxshare's 3.15B offering (Reuters)

Reuters: Five Chinese tech and advanced manufacturing companies launched Hong Kong listings today to raise up to 5.6B, led by Apple supplier Luxshare's 3.15B offering — Five Chinese technology and adv

applicationstechmeme

FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery for Wildfire Management

arXiv:2412.02831v2 Announce Type: replace-cross Abstract: The increasing accessibility of radiometric thermal imaging sensors for unmanned aerial vehicles (UAVs) offers significant potential for advan

FlatLands: Generative Floormap Completion From a Single Egocentric View

arXiv:2603.16016v2 Announce Type: replace-cross Abstract: A single egocentric image typically captures only a small portion of the floor, yet a complete metric traversability map of the surroundings w

Applications

FlexTab: A Flexible Encoder-Decoder Architecture for In-Context Learning Across Diverse Tabular Tasks

arXiv:2606.30336v1 Announce Type: new Abstract: We introduce FlexTab, a flexible encoder-decoder architecture for in-context learning on tabular data that pairs a single, task-agnostic encoder with a

applicationsarxiv-cs-lg

FlipGuard: Defending Large Language Models Against Quantization-Conditioned Backdoor Attacks

model-releasesarxiv-cs-lg

arXiv:2606.28962v1 Announce Type: cross Abstract: Model quantization is essential for the efficient deployment of Large Language Models (LLMs), but introduces a critical vulnerability: Quantization-Co

Industry

Florida bans local governments from pursuing net-zero emissions goals

HB 1217 prohibits local governments from pursuing net-zero emissions goals , with additional restrictions on carbon-trading programs, green procurement, and carbon-based taxes or fees . Governor Ron D

industryars-technica

Flow Matching in Feature Space for Stochastic World Modeling

arXiv:2606.29059v1 Announce Type: cross Abstract: World modeling requires forecasting uncertain futures while preserving information useful for downstream perception. Existing visual world models ofte

Flow Reasoning Models: Scaling Reasoning Through Iterative Self-Refinement

arXiv:2606.29150v1 Announce Type: new Abstract: Discrete flow models have recently shown promising performance on few-step text generation; however, when naively applied to structured reasoning tasks

FlowAWR: Online Adaptive Flow Reinforcement via Advantage-Weighted Rectification

arXiv:2606.30376v1 Announce Type: cross Abstract: Aligning generative flow models on continuous spaces via online reinforcement learning is constrained by intractable trajectory likelihoods. Existing

safetyarxiv-cs-cv