Search: “framework”

Convergence Analysis of the ProbAbilistic Gradient Estimator Algorithm for Weakly Convex Finite-Sum Optimization

arXiv:2509.00737v3 Announce Type: replace-cross Abstract: The ProbAbilistic Gradient Estimator algorithm (PAGE), a stochastic algorithm introduced by Li et al. in 2021, was designed to find stationary

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Conversational Human Audio-visual Talking Dialogue Generation

DGX agent

arXiv:2607.02799v1 Announce Type: new Abstract: Large-scale dyadic interactive audio-visual dialogue (DIAD) datasets provide fundamental data resources for developing humanoid interactive virtual agen

researcharxiv-cs-cv

7 Jul 2026

Correlation-Weighted Multi-Reward Optimization for Compositional Generation

arXiv:2603.18528v2 Announce Type: replace Abstract: Text-to-image models produce images that align well with natural language prompts, but compositional generation has long been a central challenge. M

Counterfactual Operator Relevance for PDE Discovery: Screening, Pruning, and Identifiability

arXiv:2506.20181v2 Announce Type: replace Abstract: We study operator relevance in data-driven partial differential equation (PDE) discovery. Sparse residual methods can select terms that improve resi

Coverage-Controlled Preference Mining from Noisy Claim Verification for Evidence-Grounded Generation

arXiv:2603.10494v2 Announce Type: replace Abstract: Evidence-grounded generation produces summaries whose claims should be supported by supplied evidence, but claim-level verifiers provide noisy feedb

safetyarxiv-cs-cl

Hardware

CPR: Chained Perceptual Refinement for Coarse-to-Fine Medical Image Classification

arXiv:2607.02591v1 Announce Type: new Abstract: High resolution medical images contain fine grained, spatially sparse cues that are critical for diagnosis, yet preserving full resolution incurs substa

hardwarearxiv-cs-cv

CRODA-ST: Single-Target Cross-Receiver Open-Set Radio Fingerprint Recognition

arXiv:2607.02567v1 Announce Type: cross Abstract: Radio frequency fingerprint identification (RFFI) provides a physical-layer credential for Internet of Things devices, but open-set decisions become f

safetyarxiv-cs-ai

Applications

Cross-device Collaborative Test-time Adaptation with Zeroth-order Optimization and Model Merging

arXiv:2607.02988v1 Announce Type: new Abstract: Test-time adaptation (TTA) mitigates domain shifts by using incoming test data to update a model on the fly. The majority of TTA methods require resourc

applicationsarxiv-cs-cv

CSympNet-ID: conformal-symplectic map learning for linearly damped Hamiltonian systems

model-releasesarxiv-cs-lg

arXiv:2607.03339v1 Announce Type: new Abstract: Learning dissipative dynamics from discrete observations is essential for reliable long-horizon prediction and physically meaningful parameter identific

CTForensics: A Comprehensive Dataset and Method for AI-Generated CT Image Detection

arXiv:2603.01878v2 Announce Type: replace Abstract: Recent advances in generative AI have made synthetic Computed Tomography (CT) images increasingly realistic, enabling promising applications in medi

Local Ai

Ctrl-Z Sampling: Scaling Diffusion Sampling with Controlled Random Zigzag Explorations

arXiv:2506.20294v5 Announce Type: replace Abstract: Diffusion models generate conditional samples by progressively denoising Gaussian noise, yet the denoising trajectory can stall at visually plausibl

local-aiarxiv-cs-cv

CuBAS: Information Geometric Curvature-Based Adaptive Sampling for Supervised Classification

arXiv:2607.03145v1 Announce Type: cross Abstract: The informativeness of a training set is as consequential as its size, yet most sampling strategies remain agnostic to the intrinsic geometry of the d

CURE: Controllable Unified Image Restoration for Complex Degradations

arXiv:2607.03044v1 Announce Type: new Abstract: The presence of composite degradations poses a significant challenge, since the underlying corruption factors exhibit complex and interdependent interac

researcharxiv-cs-cv

Current as Touch: Proprioceptive Contact Feedback for Compliant Dexterous Manipulation

arXiv:2607.03529v1 Announce Type: new Abstract: Compliance is essential for dexterous manipulation, yet existing solutions often rely on external tactile or force sensors that are costly, fragile, and

safetyarxiv-cs-ro

Curriculum-Guided Layer Scaling for Language Model Pretraining

model-releasesarxiv-cs-cl

arXiv:2506.11389v4 Announce Type: replace Abstract: As the cost of pretraining large language models grows, there is continued interest in strategies to improve learning efficiency during this core tr

Dashboard2Code: Evaluating Multimodal Models on Reconstructing Interactive Dashboards

arXiv:2607.04727v1 Announce Type: cross Abstract: Automatic data visualization generation has advanced rapidly with multi-modal large language models, yet existing efforts largely focus on static char

Applications

Data-Driven Soft Labeling Scales DNA Read Classification to Whole-Body Cell-Type Deconvolution

arXiv:2607.04987v1 Announce Type: new Abstract: Cell-type deconvolution, the task of estimating the proportions of constituent cell types in a heterogeneous biological sample, is a core problem in com

applicationsarxiv-cs-lg

DC-Motion: Decoupling Structure and Details via Discrete-Continuous Tokens for Human Motion Generation

arXiv:2606.14721v2 Announce Type: replace-cross Abstract: Text-to-motion generation requires modeling both global action structure and fine-grained motion dynamics from natural language. Existing appr

researcharxiv-cs-cv

Deep Generative Spatiotemporal Engression for Probabilistic Forecasting of Epidemics

arXiv:2603.07108v2 Announce Type: replace-cross Abstract: Accurate and reliable forecasting of epidemic incidences is critical for public health preparedness, yet it remains a challenging task due to

Deep Learning Network-Temporal Models For Traffic Prediction

arXiv:2603.11475v2 Announce Type: replace Abstract: Accurate prediction of multivariate time series is essential for emerging network intelligent control, observability, and management functions. Exis

Local Ai

DELTA-TTS: Adapting Autoregressive Model into Diffusion Language Model for Text-to-Speech

arXiv:2607.04140v1 Announce Type: cross Abstract: Autoregressive (AR) text-to-speech (TTS) models generate discrete speech tokens sequentially, which makes inference slow and can degrade robustness by

local-aiarxiv-cs-cl

Local Ai

DELTAVID: Enhancing Fine-Grained Spatiotemporal Perception with Cross-Video Differences

arXiv:2607.02551v1 Announce Type: cross Abstract: Video multimodal large language models have made strong progress on open-ended video understanding, but they still lack precise local spatiotemporal p

local-aiarxiv-cs-ai

Deterministic Envelopes for Tamed SGLD: Decoupling Stochastic Gradient Noise and Localizing Taming

arXiv:2606.05242v2 Announce Type: replace-cross Abstract: Stochastic gradient Langevin algorithms often use tamed denominators to stabilize superlinear drifts. This paper shows that when the denominat

safetyarxiv-cs-lg

Tutorials

DGSeg: Dynamic Gating of Semantic-Spatial Guided Predictions for Reasoning Segmentation

arXiv:2607.04779v1 Announce Type: new Abstract: Reasoning segmentation aims to predict pixel-wise masks for targets given complex language queries. Existing approaches leverage Multimodal Large Langua

tutorialsarxiv-cs-cv

DICT: Data Injection and Contrastive Trajectory Refinement for Conditional Image Generation with Diffusion Models

arXiv:2607.03899v1 Announce Type: new Abstract: Diffusion models have become a dominant paradigm for conditional image generation, yet existing approaches generally follow two directions: task-specifi

safetyarxiv-cs-cv

Diffusion learning reveals viable parameter manifolds and compensation geometry in biological dynamical systems

model-releasesarxiv-cs-lg

arXiv:2607.03671v1 Announce Type: cross Abstract: Models of complex systems often have many parameters, yet are constrained by far fewer experimentally accessible observables: similar activity can eme

Diffusion Models are Open-World Affordance Learners: Leveraging Generative Priors for 3D Affordance Learning

arXiv:2508.01651v2 Announce Type: replace Abstract: 3D affordance grounding aims to understand how diverse objects can be manipulated, making it a cornerstone of embodied interaction. However, prior w

Dimension Reduction for Curves: Simplified and Generalized

arXiv:2607.03112v1 Announce Type: cross Abstract: We revisit random projections for reducing the dimension of high-dimensional polygonal curves. Drawing from the toolbox of randomized linear algebra,

Direct Time-of-Flight Measurement Accuracy Improvement With Perimeter-Gated SPADs

arXiv:2607.02546v1 Announce Type: cross Abstract: Direct time of flight (dToF) measurements are susceptible to errors because of system-level and circuit-level timing jitters. In addition, device-leve

researcharxiv-cs-cv

Diverse Normal Prototypes-Guided Contrastive Reconstruction for Medical Anomaly Detection

arXiv:2508.19573v2 Announce Type: replace Abstract: Anomaly detection in medical images is challenging due to limited annotations and the domain gap. Existing reconstruction-based methods often rely o

safetyarxiv-cs-cv

Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval

arXiv:2607.04605v1 Announce Type: cross Abstract: Multi-vector vision-language retrieval preserves fine-grained visual evidence through maximum-similarity late interaction, but dense image-side tokens

Does It Fail to See or Fail to Know? Attributing Errors in Vision-Language Models

arXiv:2607.04683v1 Announce Type: cross Abstract: Vision-language models (VLMs) perform well on visual question answering with high-quality images but struggle when questions require knowledge beyond

researcharxiv-cs-cl

Don't Wait to Reply: Towards Responsive yet Thoughtful Dialogue through Proactive Thinking

arXiv:2607.03093v1 Announce Type: cross Abstract: Thinking has emerged as a critical capability for Large Language Models (LLMs) tackling complex tasks. However, its reactive nature, where reasoning i

DREAMSTEER: Latent World Models Can Steer VLA Policies During Deployment Without Any Finetuning

model-releasesarxiv-cs-ro

arXiv:2607.02865v1 Announce Type: new Abstract: Pretrained vision-language-action (VLA) policies show promising zero-shot generalization, but often fail under deployment-time distribution shift, leadi

Applications

DS-SAC: Density Search for Sample Consensus

arXiv:2607.03972v1 Announce Type: new Abstract: Robust geometric model estimation is a fundamental problem in computer vision. RANSAC and its variants remain widely used for this task; however, they r

applicationsarxiv-cs-cv

DSpark: Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation

arXiv:2607.05147v1 Announce Type: new Abstract: Speculative decoding accelerates Large Language Model (LLM) inference by decoupling draft generation from target verification. While recent parallel dra

Dual-Adaptive SAM3: Hierarchical Routing over Low-Rank Expert Layers for Parameter-Efficient Medical Image Segmentation

arXiv:2607.02571v1 Announce Type: new Abstract: The Segment Anything Model with Concepts (SAM3) heralds a new paradigm for open-vocabulary segmentation through natural language interaction, offering s

DynamiQ: Accelerating Gradient Synchronization using Compressed Multi-hop All-reduce

arXiv:2602.08923v2 Announce Type: replace Abstract: Multi-hop all-reduce is the de facto backbone of large model training. As the training scale increases, the network often becomes a bottleneck, moti

Agents

EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments

arXiv:2607.05155v1 Announce Type: new Abstract: Pretraining scaling laws reveal that model capability improves predictably with data and compute. But learning from real world environments after deploy

agentsarxiv-cs-cl

Agents

EEG-SpikeAgent: Agentic Closed-Loop Program Synthesis for Automated EEG Spike Detection

arXiv:2607.04558v1 Announce Type: cross Abstract: Automated detection of interictal epileptiform discharges in scalp electroencephalography (EEG) is clinically important, but recent high-performing de

agentsarxiv-cs-ai

Efficient Flow Matching for Sparse-View CT Reconstruction

arXiv:2603.00205v2 Announce Type: replace-cross Abstract: Generative models, particularly Diffusion Models (DM), have shown strong potential for Computed Tomography (CT) reconstruction serving as expr

Embodied Operators and Benchmarking: Toward Reusable and Deployable Embodied Intelligence Systems

arXiv:2607.03283v1 Announce Type: new Abstract: Embodied intelligence systems require not only end-to-end policy models, but also reusable functional modules that transform multimodal observations, ro

EmCom-Diffusion: Probing Visual Reflection in Emergent Languages via Image Generation

arXiv:2607.03752v1 Announce Type: cross Abstract: Measuring the extent to which emergent languages encode the visual content of their inputs is an open problem. We refer to this property as visual ref

EmoteGPT: 3D Human Facial Expressions from Natural Language Descriptions

arXiv:2607.02674v1 Announce Type: new Abstract: Precise control of 3D facial expressions from text is crucial for virtual avatars, animation, and human-computer interaction, yet existing text-to-3D me

Tutorials

Empirical Computation: Prompting versus Programming

arXiv:2503.10954v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents can solve *any* computational problem *without* an algorithm in a runtime *independent* of the computational

tutorialsarxiv-cs-ai

Enhancement of E-commerce Sponsored Search Relevancy with LLM

arXiv:2607.03886v1 Announce Type: cross Abstract: Sponsored search plays a crucial role as a revenue stream for search engines, wherein advertisers competitively bid on keywords that align with the us

Enhancing Facial Expression Recognition in Head-Mounted Displays with Synthetic Data

arXiv:2607.04490v1 Announce Type: new Abstract: Facial expression recognition (FER) is crucial for social interaction in mixed reality environments that employ head-mounted displays (HMD). However, co

safetyarxiv-cs-cv

Enhancing Implicit Neural Representations with Image Feature Embedding for Unsupervised Cardiac Cine MRI Reconstruction

arXiv:2607.04069v1 Announce Type: cross Abstract: Cardiac cine Magnetic Resonance Imaging (MRI) is a critical diagnostic tool that provides dynamic insights for radiologists. To accelerate acquisition