Search: “framework”

Jamming-Resilient PRB Reservation for Latency-Critical O-RAN Network Slicing

arXiv:2605.30622v1 Announce Type: cross Abstract: Open radio access network (O-RAN) architectures enable near real-time, software-driven control of network slicing through programmable xApps deployed

tutorialsarxiv-cs-lg

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Research

Joint Multi-Camera LiDAR Extrinsic Calibration via Learned Pairwise Initialization and Geometric Refinement

DGX agent

arXiv:2605.31576v1 Announce Type: new Abstract: Most learning-based camera-LiDAR calibration methods treat each camera-LiDAR pair independently, ignoring the rigid geometric coupling in multi-camera p

researcharxiv-cs-cv

1 Jun 2026

Hardware

Kernel Foundry: A Diagnosis-driven Evolutionary Kernel Optimizer with Multi-Experts

arXiv:2605.30359v1 Announce Type: cross Abstract: Generating high-performance GPU kernels remains challenging due to the need for both correctness and hardware-aware optimization. While large language

hardwarearxiv-cs-lg

Latent Geometric Chords for Query-Efficient Decision-Based Adversarial Attacks

arXiv:2605.31219v1 Announce Type: new Abstract: While decision-based black-box adversarial attacks present a severe security threat, current methodologies suffer from fundamental limitations. Pixel-wi

researcharxiv-cs-cv

Learning Cardiac Latent Representations in Vectorcardiogram Space

arXiv:2605.31249v1 Announce Type: cross Abstract: Electrocardiography (ECG) is a cornerstone of cardiac assessment, making the learning of informative ECG representations fundamental to tasks ranging

Learning effective Sargassum transport dynamics from limited drifter observations

arXiv:2605.30603v1 Announce Type: cross Abstract: Floating-material transport is influenced by unresolved processes that are often absent from available circulation products. We develop a data-driven

researcharxiv-cs-lg

Applications

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

arXiv:2501.12500v3 Announce Type: replace Abstract: Understanding climate dynamics requires going beyond correlations in observational data to uncover the underlying causal process. Latent drivers suc

applicationsarxiv-cs-lg

Learning Generalizable Robot Policy with Human Demonstration Video as a Prompt

arXiv:2505.20795v2 Announce Type: replace Abstract: Recent robot learning methods commonly rely on imitation learning from massive robotic dataset collected with teleoperation. When facing a new task,

safetyarxiv-cs-ro

Learning Parametric Nitrogen Fertilizer Response Curves Using Neuro Symbolic Regression

arXiv:2605.31276v1 Announce Type: new Abstract: Accurately modeling crop response to Nitrogen (N) fertilization is a fundamental challenge in precision agriculture, as it impacts both economic returns

tutorialsarxiv-cs-lg

Learning Permutation-invariant Macroscopic Dynamics

arXiv:2605.30812v1 Announce Type: new Abstract: Accurately modeling the macroscopic dynamics of high-dimensional microscopic systems is of broad interest across the sciences. Many data-driven approach

tutorialsarxiv-cs-lg

Learning Terrain-Aware Whole-Body Control for Perceptive Legged Loco-Manipulation

arXiv:2605.31343v1 Announce Type: new Abstract: Legged manipulators integrate exceptional terrain adaptability along with mobile manipulation capabilities, which make them highly promising for deploym

safetyarxiv-cs-ro

Learning to Adapt: Self-Improving Web Agent via Cognitive-Aware Exploration

arXiv:2605.31365v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have led to promising progress in web agents. However, existing web agents often rely on han

agentsarxiv-cs-ai

LiftNav: Path Planning via Semantic Lifting in TSDF-Guided Gaussian Splatting

arXiv:2605.31376v1 Announce Type: cross Abstract: Autonomous robots in unknown indoor environments require both reliable collision avoidance and object-level understanding. Classical representations s

Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models

arXiv:2605.31158v1 Announce Type: new Abstract: Interactive video world models generate video chunk by chunk in response to user-controlled camera movements, enabling applications such as real-time ga

local-aiarxiv-cs-cv

LLM Anonymization Against Agentic Re-Identificatio

arXiv:2605.30848v1 Announce Type: cross Abstract: Agentic LLMs with web search change the threat model for text anonymization: weak contextual cues can become cross-referenceable evidence for re-ident

agentsarxiv-cs-cl

LocalSUG: City-Preference-Enhanced LLM for Query Suggestion in Local-Life Services

arXiv:2603.04946v2 Announce Type: replace Abstract: In local-life service platforms, query suggestion reduces user effort by generating candidate queries from input prefixes. Traditional multi-stage s

local-aiarxiv-cs-cl

Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models

arXiv:2605.31603v1 Announce Type: cross Abstract: Connector-based video unified models have demonstrated strong capability in instruction-grounded video synthesis, but integrating a large high-fidelit

tutorialsarxiv-cs-ai

MAAT: Multi-phase Adapter-Aware Targeted Unlearning

model-releasesarxiv-cs-cl

arXiv:2605.30514v1 Announce Type: cross Abstract: Machine unlearning evaluation is structurally skewed: Why-type questions, which probe causal and relational knowledge, comprise less than 0.06% of Cou

MatchFixAgent: Language-Agnostic Autonomous Repository-Level Code Translation Validation and Repair

arXiv:2509.16187v3 Announce Type: replace-cross Abstract: Code translation transforms source code from one programming language (PL) to another. Validating the functional equivalence of translation an

agentsarxiv-cs-lg

MedFact: Benchmarking the Fact-Checking Capabilities of Large Language Models on Chinese Medical Texts

model-releasesarxiv-cs-ai

arXiv:2509.12440v3 Announce Type: replace-cross Abstract: Deploying Large Language Models (LLMs) in medical applications requires fact-checking capabilities to ensure patient safety and regulatory com

Meta-Adaptive Beam Search Planning for Transformer-Based Reinforcement Learning Control of UAVs with Overhead Manipulators under Flight Disturbances

arXiv:2603.26612v2 Announce Type: replace Abstract: Drones equipped with overhead manipulators offer unique capabilities for inspection, maintenance, and contact-based interaction. However, the motion

researcharxiv-cs-ro

MIMO: Multilingual Information Retrieval via Monolingual Objectives

model-releasesarxiv-cs-ai

arXiv:2605.31171v1 Announce Type: cross Abstract: Multilingual Information Retrieval (MLIR) reflects real-world search environments in which queries and relevant documents may appear in different lang

MindVoice: Reconstructing Intelligible Speech from Non-invasive Neural Signals with Pretrained Priors

arXiv:2605.31173v1 Announce Type: cross Abstract: Reconstructing continuous speech from non-invasive neural recordings is a fundamental problem for probing human auditory perception and building safe,

MLIPilot: LLM-Driven Auto-Research for Machine-Learned Interatomic Potentials

model-releasesarxiv-cs-lg

arXiv:2605.30889v1 Announce Type: cross Abstract: Constructing production-quality machine-learned interatomic potentials (MLIPs) requires balancing accuracy, dynamical stability, and computational thr

Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?

arXiv:2605.31036v1 Announce Type: cross Abstract: Online advertising platforms rely on machine learning models to predict click-through rates (pCTR) and conversion rates (pCVR) for auction mechanisms.

researcharxiv-cs-lg

MosaicLeaks:Privacy Risks in Querying-in-the-Open for Deep Research Agents

model-releasesarxiv-cs-cl

arXiv:2605.30727v1 Announce Type: new Abstract: Deep research agents increasingly combine private local documents with external tools like web retrieval, creating a privacy risk: an agent's external q

Motion Tracking with Muscles: Predictive Control of a Parametric Musculoskeletal Canine Model

arXiv:2506.23768v2 Announce Type: replace Abstract: We introduce a novel musculoskeletal model of a dog, procedurally generated from accurate 3D muscle meshes. Accompanying this model is a motion capt

researcharxiv-cs-ro

Multi-Turn Multi-Agent Dialogue for Collaborative Reconstruction Improves VLM Performance on Spatial Reasoning, But Only Barely

arXiv:2605.31387v1 Announce Type: new Abstract: Robots operating in diverse environments rely on visual input to interpret objects and spatial layouts. In human-collaborative tasks, they are expected

agentsarxiv-cs-cl

MultiAct: Text-to-Motion Generation from Composite Text via Tailored Attention Guidance

arXiv:2605.30925v1 Announce Type: new Abstract: Text-to-motion generation has progressed rapidly in recent years, offering an expressive interface for animation and human-computer interaction. However

researcharxiv-cs-cv

MultiPriv: Benchmarking Individual-Level Privacy Reasoning in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2511.16940v3 Announce Type: replace Abstract: Modern Vision-Language Models (VLMs) pose significant individual-level privacy risks by linking fragmented multimodal data to identifiable individua

Neuro-Symbolic Predictive Process Monitoring

arXiv:2509.00834v2 Announce Type: replace Abstract: This paper addresses the problem of suffix prediction in Business Process Management (BPM) by proposing a Neuro-Symbolic Predictive Process Monitori

local-aiarxiv-cs-ai

NTR: Neural Token Reconstruction for Scene Token Bottleneck in End-to-End Driving

arXiv:2605.31116v1 Announce Type: new Abstract: Recent perception-free end-to-end (E2E) autonomous driving methods bypass explicit perception outputs by compressing dense image patch tokens into compa

agentsarxiv-cs-cv

Applications

NumLeak: Public Numeric Benchmarks as Latent Labels in Foundation Models

arXiv:2605.30393v1 Announce Type: cross Abstract: Public numeric benchmarks appear in pretraining, so an evaluation that conditions on a date may be measuring memorized recall rather than out-of-sampl

applicationsarxiv-cs-ai

OBCache: Optimal Brain KV Cache Pruning for Efficient Long-Context LLM Inference

model-releasesarxiv-cs-ai

arXiv:2510.07651v2 Announce Type: replace-cross Abstract: Large language models (LLMs) with extended context windows enable powerful applications but impose significant memory overhead, as caching all

OmniMem: Scalable and Adaptive Memory Retrieval for Long Video Generation

arXiv:2605.30519v1 Announce Type: new Abstract: Autoregressive (AR) video generation extends videos by producing latent chunks sequentially, but scaling to long videos requires repeated access to a gr

On-Device Robotic Planning: Eliminating Inference Redundancy for Efficient Decision-Making

arXiv:2605.31460v1 Announce Type: new Abstract: Reasoning-based robotic policies using large language and vision-language models achieve strong semantic planning capabilities but mostly suffer from a

local-aiarxiv-cs-ro

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes

arXiv:2501.12020v2 Announce Type: replace Abstract: Face recognition systems (FRS) exhibit significant accuracy differences based on the user's gender. Since such a gender gap reduces the trustworthin

OpenSTBench: Beyond Semantic Evaluation for Speech Translation

arXiv:2605.30792v1 Announce Type: cross Abstract: Speech translation systems increasingly span speech-to-text translation (S2TT), speech-to-speech translation (S2ST), offline translation, and streamin

Parallel Tempering Initial Sampling in Inference-Time Reward Alignment

arXiv:2605.30991v1 Announce Type: cross Abstract: Inference-time reward alignment steers pretrained diffusion and flow-based generative models to satisfy user-specified rewards without retraining. Rec

Hardware

ParisKV: Fast and Drift-Robust KV-Cache Retrieval for Long-Context LLMs

arXiv:2602.07721v3 Announce Type: replace-cross Abstract: KV-cache retrieval is essential for long-context LLM inference, yet existing methods struggle with distribution drift and high latency at scal

hardwarearxiv-cs-cl

PatchWorld: Gradient-Free Optimization of Executable World Models

arXiv:2605.30880v1 Announce Type: cross Abstract: Text-agent environments are typically modeled as partially observable Markov decision processes (POMDPs), assuming that the simulator's latent state a

local-aiarxiv-cs-ai

Planner-Centric Reinforcement Learning for Deep Research with Structure-Aware Reward

arXiv:2605.30824v1 Announce Type: new Abstract: Deep research tasks require LLMs to plan what to investigate, retrieve evidence, and synthesize long-form answers across multiple branches of inquiry. E

Position: Quantum Kernel Machines Should Move Beyond Scalar-Valued Kernels to Realize Their Potential

arXiv:2506.03779v2 Announce Type: replace-cross Abstract: Quantum kernel functions built using quantum-mechanical principles and have emerged as a centerpiece of quantum machine learning. The initial

researcharxiv-cs-lg

Post-Training LLMs as Better Decision-Making Agents: A Regret-Minimization Approach

arXiv:2511.04393v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as 'agents' for decision-making (DM) in interactive and dynamic environments. Yet, since they

Practical Cross-Band Channel Prediction for AI-RAN via Physics-Guided Deep Unfolding

arXiv:2605.31279v1 Announce Type: cross Abstract: To make cross-band channel prediction practical for AI-native RAN, algorithms must generalize across diverse environments and support real-time infere

tutorialsarxiv-cs-ai

Preference-Aware Rubric Learning for Personalized Evaluation

arXiv:2605.31545v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve from general-purpose assistants to user-centric agents, personalization has become central to aligning model beha

safetyarxiv-cs-cl

PReMISE: Policy Rubrics as Measurement Specifications for LLM Judges

arXiv:2605.30803v1 Announce Type: new Abstract: LLM judges are increasingly used to evaluate open-ended responses, but their scores depend strongly on the rubrics that condition them. A vague rubric a

safetyarxiv-cs-ai

Applications

PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection

arXiv:2502.12119v4 Announce Type: replace-cross Abstract: Visual instruction tuning adapts pre-trained Multimodal Large Language Models (MLLMs) to follow human instructions for real-world applications

applicationsarxiv-cs-ai