Search: “framework”

DeepLatent: Think with Images via Parallel Latent Visual Reasoning

arXiv:2606.00562v1 Announce Type: new Abstract: The emerging paradigm of 'thinking with images' embeds visual states into intermediate reasoning steps, defining a new frontier for Vision-Language Mode

researcharxiv-cs-cv

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Degradation-Aware Metric Prompting for Hyperspectral Image Restoration

DGX agent

arXiv:2512.20251v3 Announce Type: replace Abstract: Unified hyperspectral image (HSI) restoration aims to recover diverse degradations within a single model. However, current methods often rely on imp

researcharxiv-cs-cv

2 Jun 2026

DeSQ: Decomposition-based SPARQL Query Generation

arXiv:2606.00203v1 Announce Type: new Abstract: Dominant approaches to Knowledge Base Question Answering (KBQA) fall into two categories. First is the generation of a formal query that suffers from br

researcharxiv-cs-cl

Disentanglement-Based Equivariant Learning for Compositional VQA

model-releasesarxiv-cs-cv

arXiv:2606.02168v1 Announce Type: new Abstract: Compositional visual question answering (VQA) represents a challenging yet fundamental task that requires models to comprehend novel combinations of pre

Tutorials

Distortion-Aware Fusion of Statistical and Vision-Language Features for Blind Image Quality Assessment

arXiv:2606.02002v1 Announce Type: new Abstract: Blind image quality assessment (BIQA) aims to predict perceived image quality without access to a reference image. Classical natural scene statistics (N

tutorialsarxiv-cs-cv

Dive into Ambiguity: A*-Inspired Multi-Agents Commonsense Obfuscation Attack on LLM Prompts

arXiv:2606.01441v1 Announce Type: new Abstract: Large language models (LLMs) excel in reasoning and knowledge-intensive tasks but remain vulnerable to prompt-level adversarial attacks that preserve in

Domain-Shift-Aware Conformal Prediction for Large Language Models

model-releasesarxiv-cs-ai

arXiv:2510.05566v2 Announce Type: replace-cross Abstract: Large language models have achieved impressive performance across diverse tasks. However, their tendency to produce overconfident and factuall

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation

arXiv:2606.00535v1 Announce Type: new Abstract: Speculative decoding (SD) has proven to be an effective technique for accelerating autoregressive generation in large language models (LLMs) however, it

researcharxiv-cs-lg

Hardware

DuetServe: Harmonizing Prefill and Decode for LLM Serving via Adaptive GPU Multiplexing

arXiv:2511.04791v2 Announce Type: replace Abstract: Modern LLM serving systems must sustain high throughput while meeting strict latency SLOs across two distinct inference phases: compute-intensive pr

hardwarearxiv-cs-lg

Dynamic Proxy-Mixing: Transferring Replay Controllers from Small to Large Models for Continual Instruction Tuning

arXiv:2606.00400v1 Announce Type: new Abstract: Continual instruction tuning updates a language model through a sequence of new domains, yet each update can progressively erode previously learned capa

Efficient Synthetic Network Generation via Latent Embedding Reconstruction

arXiv:2606.00934v1 Announce Type: cross Abstract: Network data are ubiquitous across the social sciences, biology, and information systems. Generating realistic synthetic network data has broad applic

researcharxiv-cs-lg

Efficient Weighted Sampling via Score-based Generative Models

arXiv:2502.04646v2 Announce Type: replace-cross Abstract: Weighted sampling -- sampling from a probability density function (PDF) proportional to the product of a base PDF and a weight function -- is

End-to-End Deep Learning for Predicting Metric Space-Valued Outputs

arXiv:2509.23544v2 Announce Type: replace-cross Abstract: Many modern applications involve predicting structured, non-Euclidean outputs such as probability distributions, networks, and symmetric posit

Explainable Data-driven Deep Reinforcement Learning Methods for Optimal Energy Management in Buildings

arXiv:2606.02049v1 Announce Type: new Abstract: The increasing integration of renewable energy sources into power systems, particularly in buildings equipped with photovoltaic (PV) panels and energy s

Exploiting weight-space symmetries for approximating curvature

arXiv:2606.00442v1 Announce Type: new Abstract: Many machine learning techniques rely on approximating a loss function's curvature, but this is notoriously hard to do at the scale of modern deep netwo

applicationsarxiv-cs-lg

FAIR^2 Drones: An AI-Ready Standard for Cross-Domain Wildlife Drone Datasets

arXiv:2606.00355v1 Announce Type: new Abstract: Animal ecology data collection using drones represents a substantial investment of time, expertise, and financial resources. Yet most existing datasets

researcharxiv-cs-ro

FedCF: Fair Federated Conformal Prediction

arXiv:2509.22907v2 Announce Type: replace Abstract: Conformal Prediction (CP) is a widely used technique for quantifying uncertainty in machine learning models. In its standard form, CP offers probabi

safetyarxiv-cs-lg

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

researcharxiv-cs-lg

Hardware

FLARE: Diffusion for Hybrid Language Model

arXiv:2606.01774v1 Announce Type: cross Abstract: Autoregressive (AR) large language models (LLMs) have achieved broad practical success, but sequential decoding remains a key bottleneck for low-laten

hardwarearxiv-cs-ai

Flow Matching for Convective-Scale Precipitation Downscaling

arXiv:2606.00281v1 Announce Type: cross Abstract: Generative machine learning is an increasingly important complement to dynamical downscaling for producing high-resolution precipitation projections,

Generative Multi-Robot Motion Planning via Diffusion Modeling with Multi-Agent Reinforcement Learning Guidance

arXiv:2606.00933v1 Announce Type: new Abstract: Coordinating multiple robots in shared environments requires generating feasible trajectories for each agent while accounting for interactions among age

agentsarxiv-cs-ro

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

GIFT: Geometry-Induced Functional Transfer for Category-level Object Manipulation

arXiv:2503.15371v2 Announce Type: replace-cross Abstract: Robotic manipulation of unfamiliar objects in new environments is challenging due to limited generalisation capabilities. We propose a new ski

applicationsarxiv-cs-lg

GREAT: Generalizable Backdoor Attacks in RLHF via Emotion-Aware Trigger Synthesis

arXiv:2510.09260v2 Announce Type: replace-cross Abstract: Recent work has shown that RLHF is highly susceptible to backdoor attacks. However, existing methods often rely on rare tokens or fixed trigge

Head-Pose-Aware Visual Speech Recognition with FiLM Modulation

arXiv:2606.00751v1 Announce Type: new Abstract: Visual Speech Recognition (VSR) aims to recognize speech from visual cues such as lip movements, but its performance is fundamentally limited by viseme

researcharxiv-cs-cv

Local Ai

Heterogeneous Decentralized Diffusion Models

arXiv:2603.06741v2 Announce Type: replace-cross Abstract: Training frontier-scale diffusion models often requires substantial computational resources concentrated in tightly-coupled clusters, limiting

local-aiarxiv-cs-ai

Hierarchical Semantic-Augmented Navigation: Optimal Transport and Graph-Driven Reasoning for Vision-Language Navigation

arXiv:2606.01565v1 Announce Type: cross Abstract: Vision-Language Navigation in Continuous Environments (VLN-CE) poses a formidable challenge for autonomous agents, requiring seamless integration of n

safetyarxiv-cs-cv

Hierarchically Decoupled Mixture-of-Experts for Robust Traffic Sign Recognition in Complex Driving Scenarios

model-releasesarxiv-cs-cv

arXiv:2606.01822v1 Announce Type: new Abstract: Traffic sign detection is a fundamental component of environmental perception in autonomous driving and intelligent transportation systems. However, mos

iML: Executable, Problem-Grounded, and Broadly Exploratory Code-Driven AutoML

arXiv:2602.13937v2 Announce Type: replace Abstract: Automated Machine Learning (AutoML) has improved access to machine learning, yet existing techniques often remain limited in flexibility, transparen

agentsarxiv-cs-lg

Interaction-Centered Intelligence: Toward Interaction as the Primary Unit of Analysis in Co-Creative AI and Human-AI Systems

arXiv:2606.00807v1 Announce Type: new Abstract: Traditional artificial intelligence has largely conceptualized intelligence as isolated computation occurring within bounded agents. Across classical AI

agentsarxiv-cs-ai

Interpretable Multimodal Gesture Recognition for Drone and Mobile Robot Teleoperation via Log-Likelihood Ratio Fusion

arXiv:2602.23694v3 Announce Type: replace-cross Abstract: Human operators are still frequently exposed to hazardous environments such as disaster zones and industrial facilities, where intuitive and r

Interpretable Self-Supervised Learning via Representer Landmarks and Nystrom Approximation

arXiv:2509.24467v3 Announce Type: replace Abstract: Self-supervised learning (SSL) learns representations from massive unlabeled data, yet the resulting models typically operate as black boxes, necess

safetyarxiv-cs-lg

Interpreting FCDNNs via RG on Exponential Family

arXiv:2606.00157v1 Announce Type: cross Abstract: We consider establishing the interpretability theory of deep learning through constructing a corresponding relationship between the renormalization gr

applicationsarxiv-cs-ai

LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification

arXiv:2412.12036v2 Announce Type: replace Abstract: System identification, the process of deriving mathematical models of dynamical systems from observed input-output data, has undergone a paradigm sh

agentsarxiv-cs-lg

Learning-based Directed Graph Abstraction of Combinatorial Spaces for Order-Preserving Search in Mixed-Combinatorial Nonlinear Optimization

arXiv:2606.01425v1 Announce Type: new Abstract: Mixed-combinatorial nonlinear programming (MCNLP) problems arise in many engineering design and planning applications, e.g., due to categorical, compone

Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision

arXiv:2602.20019v2 Announce Type: replace-cross Abstract: Dynamic graph anomaly detection is critical for many real-world applications but remains challenging due to the scarcity of labeled anomalies.

applicationsarxiv-cs-ai

Learning Label-Efficient Interpretable Medical Image Diagnosis via Semi-supervised Hypergraph Concept Bottleneck Model

arXiv:2606.01698v1 Announce Type: new Abstract: Deep learning has revolutionized medical image analysis, delivering exceptional diagnostic accuracy across diverse applications. Yet, the lack of interp

researcharxiv-cs-cv

Learning to Reduce Search Space for Generalizable Neural Routing Solver

arXiv:2503.03137v3 Announce Type: replace Abstract: Constructive neural combinatorial optimization (NCO) offers a promising paradigm for solving vehicle routing problems (VRPs) by directly learning to

Hardware

LithoGRPO: Fast Inverse Lithography via GRPO Reinforced Flow Matching

arXiv:2606.00228v1 Announce Type: new Abstract: In semiconductor manufacturing, lithography projects circuit layouts onto silicon wafers through an optical mask. As circuit features shrink below the w

hardwarearxiv-cs-lg

Market-Based Replanning for Safety-Critical UAV Swarms in Search and Rescue Missions

arXiv:2606.01970v1 Announce Type: new Abstract: Reliable autonomous UAV swarms in Search and Rescue (SAR) missions require fault-tolerant coordination capable of sustaining operations despite agent de

safetyarxiv-cs-ro

Med-HEAL: Analyzing and Mitigating Hallucinations in Medical LLMs with Hallucination-Aware In-Context Learning

model-releasesarxiv-cs-cl

arXiv:2606.01301v1 Announce Type: new Abstract: Hallucinations in medical large language models (LLMs) pose serious risks for clinical decision support, particularly when models must reason over compl

Medication-Aware Financial Exploitation Detection for Alzheimer's Patients Using Edge-Aware Interaction Risk Modeling

arXiv:2606.00672v1 Announce Type: new Abstract: Financial exploitation is a growing concern for people with Alzheimer's disease, especially during periods of reduced cognitive stability. Conventional

Mitigating Hallucinations in Large Language Models Via Decoder Layer Skipping

arXiv:2606.00819v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved strong performance across diverse natural language tasks, yet their outputs often suffer from hallucinations

Model-Native Computing Architecture: Envisioning Future System Architecture Through the Lens of Computer Architecture

model-releasesarxiv-cs-ai

arXiv:2606.00288v1 Announce Type: new Abstract: Large language models are undergoing a transition from model technology to system technology. As developers use Codex, Claude Code, AutoGPT, and related

Multi-modal Video Representation Alignment for Robust Self-supervised Driver Distraction Detection

arXiv:2606.02352v1 Announce Type: new Abstract: Robust self-supervised learning of multi-modal video representations is critical for real-world applications such as driver distraction detection, where

safetyarxiv-cs-cv

Multi-Objective Reinforcement Learning for Tactical Decision Making for Trucks in Highway Traffic

arXiv:2601.18783v2 Announce Type: replace-cross Abstract: Balancing safety, efficiency, and operational costs in highway driving poses a challenging decision-making problem for heavy-duty vehicles. A

NDPP-Grasp: Non-Differentiable Physical Plausibility Constraint-Guided Task-Oriented Dexterous Grasp Generation

arXiv:2606.02432v1 Announce Type: new Abstract: Task-oriented dexterous grasp generation aims to produce dexterous grasp poses that are both physically plausible and functionally suitable for specifie

safetyarxiv-cs-ro

OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents

model-releasesarxiv-cs-ai

arXiv:2606.02031v1 Announce Type: cross Abstract: Building capable visual web agents requires long-horizon reasoning, precise grounding, and robust interaction with dynamic real-world websites. Despit