Search: “research”

Fast and Lightweight Novel View Synthesis with Differentiable Multiplane Image

arXiv:2606.02068v1 Announce Type: cross Abstract: Recently, novel view synthesis has witnessed remarkable progress, with mainstream methods such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatt

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FastSLM: Hierarchical Temporal Abstraction for Efficient Long-Form Speech Adaptation

DGX agent

arXiv:2601.06199v3 Announce Type: replace-cross Abstract: Scaling Multimodal Large Language Models (MLLMs) to long-form speech is bottlenecked by the explosive growth of input tokens. Unlike images or

researcharxiv-cs-ai

2 Jun 2026

FATE-VLA:Failue-aware test generation for vision-language-action models

arXiv:2606.02307v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are increasingly used as generalist robot policies, yet their evaluation still relies largely on static benchmarks t

researcharxiv-cs-ro

Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering

arXiv:2303.04345v2 Announce Type: replace Abstract: Federated learning (FL) is a promising framework that models distributed machine learning while protecting the privacy of clients. However, FL suffe

Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning

arXiv:2412.04177v2 Announce Type: replace Abstract: Recently, there has been an increasing interest in performing post-hoc uncertainty estimation about the predictions of pre-trained deep neural netwo

FLaG: Fine-Grained Latent Grouping for Hallucination Detection

arXiv:2606.00301v1 Announce Type: new Abstract: Hallucinations in large language models (LLMs) arise from heterogeneous failure mechanisms, making reliable detection difficult for any single global un

FlatVPR: Plug-and-play Geo-linear Residual Adapter for Geometric Rectification of Foundation Model Feature Manifolds

arXiv:2606.01734v1 Announce Type: new Abstract: This paper proposes ``FlatVPR,'' a novel geometric rectification paradigm that effectively bridges the trade-off between map lightweightness and localiz

Flexible Online Representation Learning Based on Similarity Matching

arXiv:2606.01546v1 Announce Type: new Abstract: Sparse high-dimensional representations are conducive to uncovering nontrivial structures in unsupervised exploration of data. Such a representation can

FlipItRight: Stable Pose-Targeted Throw-Flip Across Diverse Objects

arXiv:2606.01713v1 Announce Type: new Abstract: We propose FlipItRight, a framework for stable planar pose-targeted throw-flip with a high-DoF manipulator. The task is decomposed into an object-level

researcharxiv-cs-ro

Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics

arXiv:2602.24201v2 Announce Type: replace Abstract: Estimating density ratios between pairs of intractable data distributions is a core problem in probabilistic modeling, enabling principled compariso

Flow-Based Generative Modeling for Optimizing Sampling Policies in Compressed Sensing Applications

arXiv:2606.00078v1 Announce Type: cross Abstract: Numerous modern applications in signal processing and medical imaging necessitate acquiring high-dimensional signals under tight resource constraints.

Flow-Transformed Implicit Processes for Function-Space Variational Inference

arXiv:2606.01954v1 Announce Type: new Abstract: Implicit-process priors define distributions over functions through flexible generative mechanisms, making them attractive for Bayesian function-space m

FlowNar: Scalable Streaming Narration for Long-Form Videos

arXiv:2606.00620v1 Announce Type: new Abstract: Recent Large Multimodal Models (LMMs), primarily designed for offline settings, are ill-suited for the dynamic requirements of streaming video. While re

FlowTime: Towards Continuous Generative Watch Time Prediction via Flow-based Personalized Priors

arXiv:2606.01352v1 Announce Type: new Abstract: Watch time has emerged as a pivotal metric for optimizing deep user engagement in short-video recommender systems. However, current methods of watch tim

FOAM: Frequency and Operator Error-Based Adaptive Damping Method for Reducing Staleness-Oriented Error for Shampoo

arXiv:2606.02365v1 Announce Type: cross Abstract: Shampoo is attracting considerable attention for its superior performance on large-scale optimization benchmarks; yet it faces a significant practical

FocusDiT: Masking Queries in Diffusion Transformers for Fine-grained Image Generation

arXiv:2606.02090v1 Announce Type: new Abstract: Diffusion transformer (DiT) has been widely adopted in the generative diffusion field, advancing the denoising of query tokens through attention and Fee

ForesightKV: Optimizing KV Cache Eviction for Reasoning Models by Learning Long-Term Contribution

arXiv:2602.03203v2 Announce Type: replace Abstract: Recently, large language models (LLMs) have shown remarkable reasoning abilities by producing long reasoning traces. However, as the sequence length

Forget Attention: Importance-Aware Attention Is All You Need

arXiv:2606.02332v1 Announce Type: new Abstract: Combining attention's global retrieval with the sequential importance signal of state space models (SSMs) is the open challenge of hybrid language model

Foundation-Preserving Adaptation via Generalized Rayleigh-Quotient Optimization

arXiv:2606.00132v1 Announce Type: cross Abstract: While finetuning effectively adapts foundation models to specialized downstream tasks, it can degrade nontarget capabilities acquired during pretraini

FOVI: A biologically-inspired foveated interface for deep vision models

arXiv:2602.03766v2 Announce Type: replace Abstract: Human vision is foveated, with variable resolution peaking at the center of a large field of view; this reflects an efficient trade-off for active s

French parsing enhanced with a word clustering method based on a syntactic lexicon

arXiv:2606.00634v1 Announce Type: new Abstract: This article evaluates the integration of data extracted from a French syntactic lexicon, the Lexicon-Grammar (Gross, 1994), into a probabilistic parser

From Extrinsic to Intrinsic: Geodesic-Guided Representation Learning for 3D Geometric Data

arXiv:2606.02268v1 Announce Type: new Abstract: Geometric analysis fundamentally distinguishes between extit{extrinsic} and extit{intrinsic} perspectives. The dominant paradigm in current 3D represent

From Global to Local: Learning Context-Aware Graph Representations for Document Classification and Summarization

arXiv:2603.00021v2 Announce Type: replace Abstract: Recent NLP systems commonly represent documents as linear token sequences. Although this captures sequential order, it can hinder modeling long-rang

From Layers to Submodules: Rethinking Granularity in Replacement-Based LLM Compression

arXiv:2606.02559v1 Announce Type: cross Abstract: Post-training compression of Large Language Models (LLMs) removes entire architectural components, either deleting them or replacing them with fitted

From Performance to Viability: A Bootstrap Framework for Latent-Space Representation Learning in Adaptive Biological Systems

arXiv:2606.01374v1 Announce Type: new Abstract: Observable performance is commonly used to characterize biological systems. In adaptive systems, however, similar performances may arise from distinct o

From Reward-Free Representations to Preferences: Rethinking Offline Preference-Based Reinforcement Learning

arXiv:2606.01123v1 Announce Type: new Abstract: Preference-based reinforcement learning (PbRL) avoids explicit reward engineering by learning from pairwise human preference feedback. Existing offline

From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection

arXiv:2602.03018v2 Announce Type: replace Abstract: Outlier detection (OD) is widely used in practice; but its effective deployment on new tasks is hindered by lack of labeled outliers, which makes al

From Zero to Hero: Training-Free Custom Concept Spawning in World Models

arXiv:2606.02575v1 Announce Type: new Abstract: Autoregressive world models have emerged as a powerful paradigm for interactive video generation, allowing users to navigate dynamically generated envir

Fundamental bounds on efficiency-confidence trade-off for transductive conformal prediction

arXiv:2509.04631v2 Announce Type: replace Abstract: Transductive conformal prediction addresses the simultaneous prediction for multiple data points. Given a desired confidence level, the objective is

GateKD: Confidence-Gated Closed-Loop Distillation for Robust Reasoning

arXiv:2605.13136v2 Announce Type: replace Abstract: Distilling multi-step reasoning abilities from large language models (LLMs) into compact student models remains challenging due to noisy rationales,

GC-MoE: Genomics-Guided Cell-Type-Specific Mixture of Experts for Histology-Based Single-Cell Spatial Transcriptomics

arXiv:2606.02424v1 Announce Type: cross Abstract: Histology-based single-cell spatial transcriptomics (ST) estimation aims to predict gene expression for individual cells from histopathological images

General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling

arXiv:2606.00110v1 Announce Type: new Abstract: Achieving robust generalization from limited data is a central challenge in embodied intelligence. Prevailing methods fail by regressing absolute coordi

Generalization Limits in Vehicle Re-Identification

arXiv:2606.01981v1 Announce Type: new Abstract: Vehicle re-identification focuses on retrieving images of the same vehicle from a gallery given a query image. Upon closer inspection of commonly used d

Generalization of Gibbs and Langevin Monte Carlo Algorithms in the Interpolation Regime

arXiv:2510.06028v3 Announce Type: replace Abstract: This paper provides data-dependent bounds on the expected error of the Gibbs algorithm in the overparameterized interpolation regime, where low trai

Generalized Guarantees for Variational Inference in the Presence of Even and Elliptical Symmetry

arXiv:2511.01064v3 Announce Type: replace-cross Abstract: Variational inference (VI) approximates a target density p by the best match q in a family of tractable distributions. The best variational ap

Generate in Reconstruction Space, Match in Semantic Space: Transport Geometry for One-Step Generation

arXiv:2606.00514v1 Announce Type: cross Abstract: Generative modeling and self-supervised representation learning (SSL) optimize structurally different objectives: generative training rewards distribu

Generative AI and Sales Productivity: Field Experiments in Online Retail

arXiv:2510.12049v4 Announce Type: replace-cross Abstract: We quantify the short-term impact of Generative Artificial Intelligence (GenAI) on sales performance through a series of large-scale randomize

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations

arXiv:2606.00248v1 Announce Type: new Abstract: Vector Symbolic Algebras (VSAs) enable robust neurosymbolic reasoning by encoding symbolic information into high-dimensional distributed representations

Geodesics with Unified Tangent-constrained Priors and Curvature Regularization

arXiv:2606.00139v1 Announce Type: cross Abstract: Curvature-penalized geodesic models have proven their effectiveness in image segmentation by computing globally optimal curves. Unfortunately, these m

Geometric Latent Reasoning Induces Shorter Generations in LLMs

arXiv:2606.02248v1 Announce Type: new Abstract: Large language models solve complex problems by generating lengthy chains of explicit reasoning tokens. While effective, this makes reasoning expensive,

GeoSAM-3D: Geodesic Prompt Propagation for Open-Vocabulary 3D Scene Segmentation from Monocular Video

arXiv:2606.00447v1 Announce Type: cross Abstract: Open-vocabulary 3D scene segmentation usually assumes RGB-D video, calibrated multi-view imagery, or a reconstructed mesh. GeoSAM-3D studies a lighter

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks

arXiv:2606.01560v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are vulnerable to adversarial attacks, which inherently invert connectivity patterns by introducing disassortative edges

Global Convergence of a Line-Search Filter Differential Dynamic Programming Method

arXiv:2606.01487v1 Announce Type: cross Abstract: In this article, we establish the global convergence properties of the FilterDDP algorithm, which extends the discrete-time differential dynamic progr

researcharxiv-cs-ro

Global Convergence of Adaptive Sensing for Principal Eigenvector Estimation

arXiv:2505.10882v2 Announce Type: replace Abstract: Principal component analysis classically requires full d-dimensional samples, yet in various applications hardware limits acquisition to a few scala

Global Geometry Is Not Enough for Vision Representations

arXiv:2602.03282v2 Announce Type: replace-cross Abstract: A common assumption in representation learning is that globally well-distributed embeddings support robust and generalizable representations.

GloResNet: A lightweight 3D CNN with global topological features for preterm brain injury prediction

arXiv:2606.02498v1 Announce Type: new Abstract: This study introduces an automated deep learning framework for predicting brain injury (BI) in preterm infants from T2-weighted MRI (dHCP dataset). We p

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation

arXiv:2606.01412v1 Announce Type: new Abstract: Post-training quantization is widely used for compressing large neural networks, but aggressive low-bit quantization can significantly degrade model qua

GRANITE : a Byzantine-Resilient Dynamic Gossip Learning Framework

arXiv:2504.17471v2 Announce Type: replace-cross Abstract: Gossip Learning (GL) is a decentralized learning paradigm where users iteratively exchange and aggregate models with a small set of neighborin