Search: “papers”

Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction

arXiv:2510.15780v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is increasingly used to support renewable energy forecasting and grid operations. As renewable penetration grows,

local-aiarxiv-cs-lg

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

DGX agent

arXiv:2606.03812v1 Announce Type: new Abstract: Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems, demand reliable hazard identifica

safetyarxiv-cs-ai

3 Jun 2026

Evaluating and Calibrating LLM Confidence on Questions with Multiple Correct Answers

model-releasesarxiv-cs-cl

arXiv:2602.07842v2 Announce Type: replace Abstract: Confidence calibration is essential for making large language models (LLMs) reliable, yet existing training-free methods have been primarily studied

Extreme Motion Generation via Hybrid Null-Space Control for Straight-Line Path Following

arXiv:2606.03390v1 Announce Type: new Abstract: This work studies ``extreme motion generation'', which aims to maximize the Cartesian path length along a pre-defined trajectory within the manipulator'

safetyarxiv-cs-ro

Fast Organic Crystal Structure Prediction with Unit Cell Flow Matching

arXiv:2606.03199v1 Announce Type: new Abstract: Organic crystal structure prediction (CSP) is a requirement for computational modelling of organic solids, but traditionally costs several CPU-years per

safetyarxiv-cs-lg

Tutorials

FCUS-rPPG: A Fast-Converging Unsupervised Framework for Remote Photoplethysmography via Gradient Oscillation Suppression

arXiv:2606.03050v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact extraction of blood volume pulse (BVP) signals using consumer-grade cameras. Recent unsupervised

tutorialsarxiv-cs-cv

FlashMLA-ETAP: Efficient Transpose Attention Pipeline for Accelerating MLA Inference on NVIDIA H20 GPUs

arXiv:2506.01969v3 Announce Type: replace-cross Abstract: Efficient inference of Multi-Head Latent Attention (MLA) is challenged by deploying the DeepSeek-R1 671B model on a single Multi-GPU server. T

FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences

arXiv:2606.03330v1 Announce Type: cross Abstract: Literature reveals that a Large Language Model's (LLM) behavior is not only conditioned by its original weights but also its instance-level parameters

researcharxiv-cs-ai

FORGE: Multi-Agent Graduated Exploitation and Detection Engineering

arXiv:2606.03453v1 Announce Type: cross Abstract: Vulnerability disclosure volumes now far exceed organizational assessment capacity, yet three adjacent research communities (proof-of-concept generati

From 3D Perception to Safety Reasoning: A Graph-Based Framework for Real-Time Underground Mine Monitoring

arXiv:2606.03460v1 Announce Type: new Abstract: Underground coal mining requires personnel and heavy equipment to operate within shared, confined, and poorly illuminated spaces where hazards such as e

local-aiarxiv-cs-cv

From Prompt to Service: An SLM-Based Agent Orchestration Gateway for AI-Driven Virtual Worlds

arXiv:2606.03557v1 Announce Type: new Abstract: As generative AI capabilities expand, AI-driven virtual worlds face a growing architectural challenge. Users interact through in-world interfaces in mul

Fully Automated Identification of Lexical Alignment and Preference-Stage Shifts in Large Language Models

arXiv:2606.03165v1 Announce Type: cross Abstract: The language used by digital chat assistants such as ChatGPT can diverge from human expectations (misalignment). Research, mostly on Scientific Englis

G^2C-MT: Graph-Guided Context Selection for Document-Level Machine Translation

model-releasesarxiv-cs-cl

arXiv:2606.03078v1 Announce Type: new Abstract: Effective document-level machine translation (DocMT) requires capturing long-range discourse dependencies. Recent work has explored retrieval-based and

Graph Mamba Survival Analysis Based on Topology-Aware ordering

arXiv:2606.02602v1 Announce Type: cross Abstract: In computational pathology, Whole Slide Images (WSIs) survival analysis is crucial for patient prognosis assessment, but it faces multiple technical c

researcharxiv-cs-cv

Greener Than Humans? Environmental Attitudes in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.02741v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in sustainability-related decision support, reporting, and public communication, yet little systemati

Applications

Hierarchical Federated Learning with Dynamic Clustering and Adaptive Regularization for Robust Infrastructure Inspection

arXiv:2606.03084v1 Announce Type: new Abstract: The deployment of data-driven computer vision models for structural health monitoring (SHM) is heavily constrained by the data silo dilemma due to strin

applicationsarxiv-cs-cv

Human-Like Goalkeeping in a Realistic Football Simulation: a Sample-Efficient Reinforcement Learning Approach

arXiv:2510.23216v4 Announce Type: replace Abstract: While several high profile video games have served as testbeds for Deep Reinforcement Learning (DRL), this technique has rarely been employed by the

Human2Humanoid: Physics-Aware Cross-Morphology Motion Retargeting for Humanoid Robots

arXiv:2606.03476v1 Announce Type: new Abstract: Retargeting human motion to humanoid robots is critical for teleoperation, imitation learning and human-robot interaction. However, it remains challengi

researcharxiv-cs-ro

Applications

Hybrid Adaptive Kalman Filtering for Data-Efficient Joint Tracking and Classification

arXiv:2606.02767v1 Announce Type: cross Abstract: Kalman filtering performance is highly sensitive to model mismatch and noise covariance tuning. Learning-based approaches address these limitations bu

applicationsarxiv-cs-lg

Inference-Time Scaling for Joint Audio-Video Generation

arXiv:2606.03183v1 Announce Type: cross Abstract: Joint audio-video generation aims to synthesize realistic audio-video pairs that are both semantically aligned with text prompts and precisely synchro

safetyarxiv-cs-cv

Laplacian Representations for Decision-Time Planning

arXiv:2602.05031v2 Announce Type: replace Abstract: Planning with a learned model remains a key challenge in model-based reinforcement learning (RL). In decision-time planning, state representations a

Leave it to the Specialist: Repair Sparse LLMs with Sparse Fine-Tuning via Sparsity Evolution

arXiv:2505.24037v3 Announce Type: replace Abstract: Sparse large language models (LLMs) offer an attractive direction toward efficient deployment, but adapting them to downstream tasks remains challen

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems

arXiv:2606.03834v1 Announce Type: new Abstract: Flow matching has recently emerged as a powerful approach for imitation learning, enabling scalable, expressive, and multimodal motion policies. However

Letting Tutor Personas Speak Up for LLMs: Learning Steering Vectors from Dialogue via Preference Optimization

arXiv:2602.07639v2 Announce Type: replace Abstract: With the emergence of large language models (LLMs) as a powerful class of generative artificial intelligence (AI), their use in tutoring has become

safetyarxiv-cs-cl

Locality Does Not Imply Reachability: Boundary Repair in Block-Sparse Causal Attention

arXiv:2606.02680v1 Announce Type: new Abstract: Sparse causal attention is usually described by sequence locality: nearby tokens should remain easy to access, while distant tokens may be dropped to re

LoCAtion: Long-time Collaborative Attention Framework for High Dynamic Range Video Reconstruction

arXiv:2603.14377v2 Announce Type: replace Abstract: Prevailing High Dynamic Range (HDR) video reconstruction methods are fundamentally trapped in a fragile alignment-and-fusion paradigm. While explici

safetyarxiv-cs-cv

MariData: One-Step Unpaired Image Translation for Maritime Environments

arXiv:2606.03246v1 Announce Type: new Abstract: The development on robust perception systems for Maritime Autonomous Surface Ships (MASS) is heavily constrained by the scarcity of diverse training dat

agentsarxiv-cs-cv

Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective

arXiv:2606.03290v1 Announce Type: cross Abstract: Graph Foundation Models (GFMs), built upon the Pre-training and Adaptation paradigm, have emerged as a research hotspot in graph learning. For GNN-bas

Motion Planning in Dynamic Environments: A Survey from Classical to Modern Methods

arXiv:2606.02677v1 Announce Type: new Abstract: Motion planning in dynamic environments requires robots to continuously adapt their paths in response to environmental changes for safe and uninterrupte

researcharxiv-cs-ro

Multi-component Causal Tracing in Large Language Models

arXiv:2606.03085v1 Announce Type: cross Abstract: Causal tracing systematically intervenes on a large language model's (LLM's) internal representations to uncover and quantify the causal pathways link

safetyarxiv-cs-cl

Multi-Segment Attention: Enabling Efficient KV-Cache Management for Faster Large Language Model Serving

arXiv:2606.02964v1 Announce Type: cross Abstract: Large Language Model (LLM) inference relies on key-value (KV) caches to avoid redundant attention computation. While approximate KV cache retention te

safetyarxiv-cs-cl

Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models

arXiv:2602.03681v2 Announce Type: replace Abstract: The quadratic computational complexity of softmax transformers has become a bottleneck in long-context scenarios. In contrast, linear attention mode

researcharxiv-cs-cl

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration

arXiv:2507.23035v4 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated impressive capabilities across a wide range of applications, but demand substantial memory and comput

OpenAgenet/OAN: Open Infrastructure for Trusted Agent Interconnection

arXiv:2606.03161v1 Announce Type: cross Abstract: OpenAgenet, abbreviated as OAN, is an open infrastructure project for trusted Agent interconnection. It addresses a problem that becomes visible when

OpenEAI-Platform: An Open-source Embodied Artificial Intelligence Hardware-Software Unified Platform

arXiv:2606.03392v1 Announce Type: new Abstract: Embodied AI in the real world requires both accurate hardware and robust vision-language-action (VLA) policies. We present OpenEAI-Platform, a fully ope

Outsmarting the Chameleon: Counterfactual Decoupling for Tactical OOD Shifts in Live Streaming Risk Assessment

arXiv:2606.02946v1 Announce Type: new Abstract: Live streaming has emerged as a primary medium for social interaction and digital commerce, yet it is increasingly plagued by sophisticated risks. A fun

Overlaying Governance: A Compositional Authorization Framework for Delegation and Scope in Agentic AI

arXiv:2606.03518v1 Announce Type: new Abstract: As AI systems evolve from passive models into autonomous active agents capable of initiating actions, collaborating, and delegating tasks, the tradition

Patcher: Post-Hoc Patching of Backdoored Large Language Models

arXiv:2606.02995v1 Announce Type: cross Abstract: Large language models remain vulnerable to jailbreak backdoor attacks, where adversaries poison safety alignment data to embed hidden triggers that by

local-aiarxiv-cs-ai

PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion

arXiv:2606.03441v1 Announce Type: cross Abstract: Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to th

Position: Adversarial ML for LLMs Is Not Making Any Progress

arXiv:2502.02260v2 Announce Type: replace Abstract: In the past decade, considerable research effort has been devoted to securing machine learning (ML) models that operate in adversarial settings. Yet

Privacy-Robust Incrementality Measurement for Advertising Systems under Signal Loss

arXiv:2606.03878v1 Announce Type: cross Abstract: Advertising platforms use randomized lift tests to measure incrementality, but privacy-preserving reporting systems degrade the observed signal throug

Tutorials

Re-Evaluating Continual Learning with Few-Shot Adaptation

arXiv:2606.03843v1 Announce Type: cross Abstract: Continual learning methods aim to maximize the stability and plasticity of machine learning models that are trained on a sequence of tasks. The standa

tutorialsarxiv-cs-ai

Regime-Arrival Uncertainty in Generalization Bounds under Distribution Shift

arXiv:2606.02657v1 Announce Type: new Abstract: The standard generalization bounds assume that the training and deployment distributions are the same, or are static, and don't consider regime switchin

Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding

arXiv:2606.03080v1 Announce Type: cross Abstract: Causal language models factorize sequence probabilities using only preceding context, leaving future information unexploited during training despite i

local-aiarxiv-cs-ai

Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps

arXiv:2606.03421v1 Announce Type: new Abstract: Specular glare on reflective floors, glass boundaries, and glossy indoor surfaces frequently corrupts active-stereo RGB-D depth measurements, producing

Reproducibility is the New Copyleft: Defining AGI-oriented Reproducible Builds

arXiv:2606.03019v1 Announce Type: cross Abstract: Copyleft, as implemented in licenses such as the GNU General Public License, was a legal hack that used copyright to guarantee user freedom by tying t

ResCLIP: Residual Attention for Training-free Dense Vision-language Inference

arXiv:2411.15851v2 Announce Type: replace Abstract: While vision-language models like CLIP have shown remarkable success in open-vocabulary tasks, their application is currently confined to image-leve

local-aiarxiv-cs-cv

Revisiting Embodied Chain-of-Thought for Generalizable Robot Manipulation

arXiv:2606.03784v1 Announce Type: new Abstract: Embodied chain-of-thought (CoT) aims to bridge linguistic reasoning and robotic control, but its effective form and integration strategy remain underexp