Search: “framework”

HyWorldVLA: A Vision-Language-Action Model with Hybrid World Modeling for Autonomous Driving

arXiv:2607.20988v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models augmented with world modeling represent a promising paradigm for end-to-end autonomous driving. While pixel-level

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Identifying Good Rules for Efficient SAT Encodings of Single-Constant Multiplication Using Machine Learning

DGX agent

arXiv:2607.21188v1 Announce Type: new Abstract: The Single Constant Multiplication problem is a fundamental NP-hard optimization task in hardware design, which seeks to decompose a fixed constant usin

researcharxiv-cs-ai

24 Jul 2026

Improving Access to Essential Medicines via Decision-Aware Machine Learning

arXiv:2607.20542v1 Announce Type: cross Abstract: A critical challenge in healthcare systems in low- and middle-income countries (LMICs) is the efficient and equitable allocation of scarce resources,

InferenceBench: A Benchmark for Open-Ended LLM Inference Optimization by AI Agents

arXiv:2607.20468v1 Announce Type: new Abstract: AI agents are increasingly used to automate research and development tasks, yet existing benchmarks typically evaluate them on prescribed workflows or n

IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests

arXiv:2607.20759v1 Announce Type: cross Abstract: AI coding agents powered by LLMs are increasingly integrated into real-world software development, where they generate, edit, and execute code with au

Joint Utilization of Geospatial and census proxies for Autoencoder-Assisted Downscaling (JUGAAD) of socioeconomic indicators in India

arXiv:2607.20559v1 Announce Type: cross Abstract: Monitoring poverty and food security indicators is imperative for addressing socioeconomic challenges in developing nations. A limitation is mismatche

Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations

arXiv:2607.20426v1 Announce Type: cross Abstract: Existing LLM hallucination mitigation methods, including prompt engineering and model optimization, either hardly alter models'internal knowledge or h

Latent Variable-Mediated Cross-Learning for Few-Shot Acoustic Impedance Imaging

arXiv:2607.20989v1 Announce Type: new Abstract: Acoustic impedance imaging is a fundamental yet severely ill-posed problem in subsurface analysis: the seismic wavelet is unknown, observations are band

Learning-based Seam Correspondence Reconstruction in Sewing Patterns

arXiv:2607.21213v1 Announce Type: new Abstract: Digital sewing patterns typically consist of disjoint 2D panels without explicit stitch annotations, making downstream 3D modeling reliant on labor-inte

LLMs Get Lost in Evolving User Intent

arXiv:2607.20734v1 Announce Type: new Abstract: As LLMs become more capable, they are increasingly deployed as collaborative agents, taking on user-delegated tasks through iterative interaction. Yet g

tutorialsarxiv-cs-lg

M^3-Gen: Interpretable Multimodal Generation of Gene Expression Profiles Using Clinical and Imaging Data

arXiv:2607.21343v1 Announce Type: cross Abstract: Integrating heterogeneous biomedical data, including clinical metadata, histopathology images, and molecular profiles, is crucial for comprehensive di

tutorialsarxiv-cs-ai

MAGE-Vein: Multi-Instance Age and Gender Estimation from Finger Vein Images

arXiv:2607.20897v1 Announce Type: new Abstract: Age estimation from finger vein images has been widely considered impractical due to severe demographic biases in public datasets and physiological conf

MagicMakeup: A Region-Controllable Diffusion Transformer for High-Fidelity Makeup-Transfer

model-releasesarxiv-cs-cv

arXiv:2607.20924v1 Announce Type: new Abstract: Makeup-transfer applies the reference makeup to the source face while preserving the source identity. Despite advances in full-face editing by diffusion

MedGame: Storytelling Gamification Empowered by Large Language Models for Medical Education

model-releasesarxiv-cs-cl

arXiv:2607.21570v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise for medical education, but most existing systems focus on localized interactions such as question answering or

Memory-Computation Tradeoffs in Semi Amortized Parametric Optimization

model-releasesarxiv-cs-lg

arXiv:2607.20769v1 Announce Type: new Abstract: Learning-enabled decision systems often use offline data or computation to reduce online compute cost. Despite the empirical success of such approaches,

Agents

MiniCache: Reusable Program Caching with Small Model Interfaces for Efficient LLM Inference

arXiv:2607.20507v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for program-aided reasoning, agentic decision making, and structured task execution, but these applic

agentsarxiv-cs-ai

Hardware

ModelExpress: Distributing Model Artifacts at the Speed of Light

NVIDIA ModelExpress (MX) is an agentic AI platform that streamlines the lifecycle of large‑model weights by automatically locating and using the fastest path to load them—prioritizing GPU‑to‑GPU P2P R

hardwarenvidia-developer

MSBraM: A Multi-scale Self-supervised Brain Foundation Model for Hierarchical EEG Dynamics Learning

arXiv:2607.21402v1 Announce Type: new Abstract: Self-supervised foundation models have recently shown strong potential for electroencephalogram (EEG)-based analysis. However, existing approaches strug

local-aiarxiv-cs-ai

Multi-turn RL with Structural and Performance Aware Rewards for CUDA Kernel Generation

arXiv:2607.20908v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful technique to enhance the reasoning capacity of LLMs for optimized code

Multimodal CoLRAG-TF: Triple-Filtered Retrieval for Complex PDFs

model-releasesarxiv-cs-lg

arXiv:2607.20517v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) over heterogeneous PDF collections remains challenging due to multimodal content, domain-specific terminology, and

Hardware

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

arXiv:2607.20709v1 Announce Type: new Abstract: Traditional agent development is split across prompt templates, tool schemas, callback code, and workflow graphs. We present NVIDIA Object-Oriented Agen

hardwarearxiv-cs-ai

One Round Is All You Need: Analytic Federated Learning for Task-Heterogeneous Multi-Label Medical Image Classification

arXiv:2607.20641v1 Announce Type: new Abstract: Federated learning (FL) enables multiple clinical institutions to collaboratively train a shared disease classifier without centralizing patient data. I

safetyarxiv-cs-lg

Out of Sight, Still in Mind: Token Compression for Omni-LLMs

arXiv:2607.21179v1 Announce Type: new Abstract: The goal of this paper is to reduce the input token cost of Omni-modal large language models (Omni-LLMs) at inference time. Omni-LLMs reason jointly ove

PATS: Policy-Aware Training Scaffolding for Agentic Reinforcement Learning

arXiv:2607.21419v1 Announce Type: new Abstract: In long-horizon LLM agent reinforcement learning, weak policies often repeat similar failures, producing uninformative rollout trajectories and limiting

safetyarxiv-cs-ai

PC-Edit: Prompt-Contrastive Region Discovery and Region-Guided Editing

arXiv:2607.21318v1 Announce Type: cross Abstract: Replacing an object with one that differs in category or shape requires complete source removal, natural target formation unconstrained by the source

PersonaTrail: Benchmarking Personalized Web Agents through Browsing Trails

arXiv:2607.20482v1 Announce Type: new Abstract: Recent advances in large language models have enabled web agents to autonomously execute complex tasks. In practice, users frequently provide underspeci

PISmith: Reinforcement Learning-based Red Teaming for Prompt Injection Defenses

model-releasesarxiv-cs-lg

arXiv:2603.13026v2 Announce Type: replace Abstract: Prompt injection poses serious security risks to real-world LLM applications, particularly autonomous agents. Although many defenses have been propo

PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs

arXiv:2607.20470v1 Announce Type: new Abstract: Enhancing the task-specific capabilities of Large Language Models (LLMs) primarily requires substantial instruction-tuning datasets. However, the sheer

Position Bias is Hidden Behind Ceiling Effects: A Permutation Diagnostic for LLM Benchmarks

model-releasesarxiv-cs-cl

arXiv:2607.20864v1 Announce Type: cross Abstract: Position bias in multiple-choice LLM evaluation is widely cited as a confound in capability comparisons, but published measurements rely on single ans

Position: Natural Language Should Not Fully Replace Formal Languages

arXiv:2607.20432v1 Announce Type: new Abstract: Recent advances in large language models and their widespread adoption have prompted claims that natural language could entirely replace formal language

applicationsarxiv-cs-cl

PrefReward: Learning User Preference Matrix for Personalized Text Generation

arXiv:2607.21067v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable ability in generating personalized content by leveraging user histories and contextual cues. H

tutorialsarxiv-cs-cl

Probabilistic Physics-Aware Machine Learning Predictions of Electric Truck Energy Consumption with Field Data

arXiv:2607.19054v2 Announce Type: replace Abstract: In this work, we incorporate first principle physics into the construction of data-driven methods by considering a model that accounts for the diffe

tutorialsarxiv-cs-lg

Profiling Lightweight Large Language Models

arXiv:2607.20806v1 Announce Type: new Abstract: Lightweight large language models (LLMs) are increasingly being deployed locally on personal computers and are expected to play a growing role in resour

QATMA: Quantization-Aware Training with Multimodal Alignment for Open-Vocabulary Object Detection

arXiv:2603.05964v3 Announce Type: replace Abstract: Quantizing open-vocabulary object detection (OVOD) models reduces their memory and computational costs, but extremely low-bit quantization severely

safetyarxiv-cs-cv

RadioTrace: Transmitter-Aware Diffusion for Radio Map Estimation without Deployment-Time Fine-Tuning

arXiv:2607.20909v1 Announce Type: cross Abstract: Radio map (RM) estimation aims to reconstruct the spatial distribution of wireless signal characteristics, such as received signal strength (RSS), fro

local-aiarxiv-cs-lg

RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring

arXiv:2607.20628v1 Announce Type: cross Abstract: Real-world video deblurring remains challenging due to diverse motion patterns, complex degradations, and the scarcity of realistic training data, yet

Agents

RECO: Region-Aware Compensation for Extrinsic Perturbations in Roadside 3D Detection

arXiv:2607.20947v1 Announce Type: new Abstract: In intelligent transportation systems, roadside 3D object detection provides wide-area perception crucial for traffic understanding, cooperative early w

agentsarxiv-cs-cv

REFACT: Adaptive Fact Restatement for Compact and Faithful Chain-of-Thought Reasoning

arXiv:2607.20833v1 Announce Type: new Abstract: Large language models increasingly rely on long-form reasoning for complex tasks, yet their reasoning traces may drift away from the supplied context wh

local-aiarxiv-cs-cl

Regularized Optimization on Grassmann Manifold: Theory, Algorithm and Applications

arXiv:2607.21039v1 Announce Type: new Abstract: Spectral methods are among the most widely used techniques for community detection, clustering, and graph learning. Their performance, however, critical

applicationsarxiv-cs-lg

Relative Value Learning

arXiv:2607.21120v1 Announce Type: cross Abstract: In reinforcement learning, critics typically estimate absolute state values V(s), estimating how good a particular situation is in isolation. However,

Riemannian Deep Learning: Modules, Networks, and Geometries

arXiv:2607.19305v2 Announce Type: replace-cross Abstract: Deep neural networks on manifold-valued representations have attracted growing interest, but many basic components remain tied to specific man

Routing Without Training: Controllable-Ratio LLM Offloading via Reliability Gating

arXiv:2607.20481v1 Announce Type: new Abstract: Local-cloud collaboration is a practical way to deploy large language models under resource constraints, but existing methods often rely on trained rout

local-aiarxiv-cs-ai

Safety-oriented sidewalk and road segmentation for smartphone-based assistive navigation

arXiv:2607.21137v1 Announce Type: new Abstract: Independent sidewalk mobility is essential for blind and visually impaired pedestrians (BVIPs), yet smartphone-based assistive navigation requires perce

safetyarxiv-cs-cv

SAGE: A Socially-Aware Generative Engine for Heterogeneous Multi-Agent Navigation

arXiv:2607.16619v2 Announce Type: replace Abstract: Safe and socially compliant navigation in open human-robot environments requires robots to reason about heterogeneous participants with different dy

safetyarxiv-cs-ro

SalesLoop: Reinforcement Learning from Performance Feedback for Sales Lead Ranking

arXiv:2607.20655v1 Announce Type: cross Abstract: Lead ranking in Customer Relationship Management (CRM) systems faces a persistent challenge: models achieving high offline accuracy often underperform

safetyarxiv-cs-ai

Scaling Up Formal Representation of Clinical Trial Protocols in Ensemble Logic Using LLMs: A Preliminary Study

arXiv:2607.21307v1 Announce Type: cross Abstract: The reliance on unstructured free text for documenting clinical trial protocols creates a significant barrier to automated reasoning, cohort discovery

Self-Supervised Bio-Inspired Robotic Trajectory Planning with Obstacle Avoidance

arXiv:2607.20743v1 Announce Type: cross Abstract: Trajectory planning is a fundamental problem in robotics, requiring the generation of collision-free and efficient trajectories in a potentially compl

Semantic-Aware Task Clustering for Constructive and Cooperative Multi-Tasking

arXiv:2607.21426v1 Announce Type: new Abstract: Cooperative multi-task semantic communication (CMT-SemCom) improves task execution performance by leveraging shared representations. However, as we demo

researcharxiv-cs-lg