Search: “inference”

On-Device Interpretable Tsetlin Machine-Based Intrusion Detection for Secure IoMT

arXiv:2605.16707v1 Announce Type: cross Abstract: The rapid evolution of digital health technologies is redefining healthcare services worldwide. The integration of wireless communication and Internet

local-aiarxiv-cs-lg

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OpenJarvis: Personal AI, On Personal Devices

DGX agent

arXiv:2605.17172v1 Announce Type: cross Abstract: Personal AI stacks, like OpenClaw and Hermes Agent, are becoming central to daily work, yet they route nearly every query (often over sensitive local

model-releasesarxiv-cs-ai

19 May 2026

OProver: A Unified Framework for Agentic Formal Theorem Proving

arXiv:2605.17283v1 Announce Type: cross Abstract: Recent progress in formal theorem proving has benefited from large-scale proof generation and verifier-aware training, but agentic proving is rarely i

OrbiSim: World Models as Differentiable Physics Engines for Embodied Intelligence

arXiv:2605.16395v1 Announce Type: cross Abstract: We present OrbiSim, a novel robotic simulation paradigm that redefines world models as a fully differentiable physics engine for embodied intelligence

safetyarxiv-cs-lg

Overeager Coding Agents: Measuring Out-of-Scope Actions on Benign Tasks

model-releasesarxiv-cs-ai

arXiv:2605.18583v1 Announce Type: cross Abstract: Coding agents now run autonomously with shell, file, and network privileges. When a user issues a benign request, the agent sometimes does more than a

PAIR: Prefix-Aware Internal Reward Model for Multi-Turn Agent Optimization

arXiv:2605.17877v1 Announce Type: new Abstract: A significant hurdle for current LLMs is the execution of complex, multi-stage tasks. Group Relative Policy Optimization (GRPO) has been emerging as a l

Pedestrian-Aware LLM-Driven Behavioral Planning for Autonomous Vehicles

arXiv:2605.16858v1 Announce Type: cross Abstract: Autonomous Vehicles (AVs) must make reliable decisions in dense urban environments where pedestrian behavior is variable, sometimes abnormal, and ofte

Physics-Guided Geometric Diffusion for Macro Placement Generation

arXiv:2605.16451v1 Announce Type: cross Abstract: Macro placement is a pivotal stage in VLSI physical design, fundamentally determining the overall chip performance. Recent data-driven placement metho

PIXLRelight: Controllable Relighting via Intrinsic Conditioning

arXiv:2605.18735v1 Announce Type: new Abstract: We present PIXLRelight, a feed-forward approach for physically controllable single-image relighting. Existing methods either provide limited lighting co

Policy-Grounded Dynamic Facet Suggestions for Job Search

arXiv:2605.16479v1 Announce Type: cross Abstract: Job seekers often initiate search with short, underspecified queries. At LinkedIn, over 80% of job-related queries contain three or fewer keywords, ma

Position: Age Estimation Models Do Not Process Biometric Data

arXiv:2605.17347v1 Announce Type: cross Abstract: When a neural network estimates someone's age from a photograph, does it process biometric data? The answer depends on whether identity-discriminative

Preference Instability in Reward Models: Detection and Mitigation via Sparse Autoencoders

arXiv:2605.16339v1 Announce Type: new Abstract: Preference learning in large language models relies on reward models as proxies for human judgment. However, these models frequently exhibit preference

researcharxiv-cs-lg

PROTEA: Offline Evaluation and Iterative Refinement for Multi-Agent LLM Workflows

arXiv:2605.18032v1 Announce Type: cross Abstract: Multi-agent LLM workflows -- systems composed of multiple role-specific LLM calls -- often outperform single-prompt baselines, but they remain difficu

local-aiarxiv-cs-ai

Proximal-IMH: Proximal Posterior Proposals for Independent Metropolis-Hastings with Approximate Operators

arXiv:2602.21426v2 Announce Type: replace Abstract: We consider the problem of sampling from a posterior distribution arising in Bayesian inverse problems in science, engineering, and imaging. Our met

local-aiarxiv-cs-lg

PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship

arXiv:2605.17679v1 Announce Type: cross Abstract: Cancer survivors face elevated rates of depression, anxiety, and general emotional distress, yet the precise moments they most need support are often

RAPT: Retrieval-Augmented Post-hoc Thresholding for Multi-Label Classification

arXiv:2605.16535v1 Announce Type: cross Abstract: Industrial multi-label document understanding pipelines score candidate labels and threshold or rank them to form a label set per document. This early

local-aiarxiv-cs-ai

Reasoning Can Be Restored by Correcting a Few Decision Tokens

arXiv:2605.16874v1 Announce Type: new Abstract: Large reasoning models (LRMs) substantially outperform their base LLM counterparts on challenging reasoning benchmarks, yet it remains poorly understood

tutorialsarxiv-cs-ai

ReBaR: Reference-Based Reasoning for Robust Pose Estimation from Monocular Images

model-releasesarxiv-cs-cv

arXiv:2303.11675v3 Announce Type: replace Abstract: R}easoning for Robust Human Pose and Shape Estimation), designed to estimate human body shape and pose from single-view images. ReBaR effectively ad

Reconciling Contradictory Views on the Effectiveness of SFT in LLMs: An Interaction Perspective

arXiv:2605.17967v1 Announce Type: new Abstract: This paper explores a scientific question in supervised fine-tuning (SFT): why SFT is broadly effective for small-scale deep neural networks, yet can pr

Resolving Representation Ambiguity in Feedforward Novel View Synthesis Transformer via Semantic-Spatial Decoupling

arXiv:2605.18599v1 Announce Type: new Abstract: Transformer-based models have advanced feedforward novel view synthesis (NVS). Current architectures such as GS-LRM and LVSM mix semantic information (e

Rethinking Table Pruning in TableQA: From Sequential Revisions to Gold Trajectory-Supervised Parallel Search

arXiv:2601.03851v2 Announce Type: replace Abstract: Table Question Answering (TableQA) benefits significantly from table pruning, which extracts compact sub-tables by eliminating redundant cells to st

researcharxiv-cs-cl

Rethinking the State Update Gate for Long-Sequence Recurrent 3D Reconstruction

arXiv:2605.16981v1 Announce Type: new Abstract: Streaming 3D reconstruction under a strict constant-memory budget hinges on how the recurrent state is updated as the stream evolves. We profile TTT3R-s

Retrieval-Based Multi-Label Legal Annotation: Extensible, Data-Efficient and Hallucination-Free

model-releasesarxiv-cs-cl

arXiv:2605.16767v1 Announce Type: new Abstract: Multi-label legal annotation requires assigning multiple labels from large, evolving taxonomies to long, fact-intensive documents, often under limited s

Rover: Context-aware Conflict Resolution with LLM

arXiv:2605.17279v1 Announce Type: cross Abstract: Code merging is a significant challenge, particularly in large-scale projects. Existing solutions, including program analysis and machine learning, sh

tutorialsarxiv-cs-ai

SAFE-SVD: Sensitivity-Aware Fidelity-Enforcing SVD for Physics Foundation Models

arXiv:2605.17985v1 Announce Type: cross Abstract: We propose a new method for compressing physics foundation models (PFMs) which is a new trend in AI for Science. While model compression is essential

Safety Geometry Collapse in Multimodal LLMs and Adaptive Drift Correction

arXiv:2605.18104v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) often fail to transfer safety capabilities learned in the text modality to semantically equivalent non-text inp

SAMRI: Segment Any MRI

arXiv:2510.26635v3 Announce Type: replace-cross Abstract: Summary: SAMRI is an MRI-specialized adaptation of the Segment Anything Model achieving superior whole-body MRI segmentation, particularly for

local-aiarxiv-cs-cv

Scalable Knowledge Editing for Mixture-of-Experts LLMs via Tensor-Structured Updates

arXiv:2605.16686v1 Announce Type: new Abstract: Knowledge editing (KE) provides a lightweight alternative to repeated fine-tuning of LLMs. However, most existing KE methods target dense feed-forward l

SCAR: Self-Supervised Continuous Action Representation Learning

arXiv:2605.16412v1 Announce Type: cross Abstract: Despite the central role of action in embodied intelligence, learning transferable action representations from visual transitions remains a fundamenta

SE-GA: Memory-Augmented Self-Evolution for GUI Agents

arXiv:2605.16883v1 Announce Type: new Abstract: Autonomous Graphical User Interface (GUI) agents often struggle with multi-step tasks due to constrained context windows and static policies that fail t

See What I Mean: Aligning Vision and Language Representations for Video Fine-grained Object Understanding

arXiv:2605.18018v1 Announce Type: cross Abstract: We present SWIM (See What I Mean), a novel training strategy that aligns vision and language representations to enable fine-grained object understandi

local-aiarxiv-cs-ai

SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation

arXiv:2605.17630v1 Announce Type: new Abstract: Here's a trimmed version under 1920 characters: Open-vocabulary segmentation models such as SAM3 achieve strong performance through concept-level text p

Self-Play Only Evolves When Self-Synthetic Pipeline Ensures Learnable Information Gain

model-releasesarxiv-cs-ai

arXiv:2603.02218v2 Announce Type: replace-cross Abstract: Large language models (LLMs) make it plausible to build systems that improve through self-evolving loops, but many existing proposals are bett

Self-Supervised Bootstrapping of Action-Predictive Embodied Reasoning

arXiv:2602.08167v2 Announce Type: replace-cross Abstract: Embodied Chain-of-Thought (CoT) reasoning has significantly enhanced Vision-Language-Action (VLA) models, yet current methods rely on rigid te

SGSoft: Learning Fused Semantic-Geometric Features for 3D Shape Correspondence via Template-Guided Soft Signals

arXiv:2605.18039v1 Announce Type: new Abstract: Learning dense correspondences across deformable 3D shapes remains a long-standing challenge due to structural variability, non-isometric deformation, a

SHED: Style-Homogenized Embedding Alignment for Domain Generalization

arXiv:2605.16973v1 Announce Type: new Abstract: Domain generalization aims to enhance model robustness against unseen domains with embedding distribution shifts. While large-scale vision-language mode

Skim: Speculative Execution for Fast and Efficient Web Agents

arXiv:2605.16565v1 Announce Type: new Abstract: Skim is a speculative execution framework for web agents that exploits the predictable structure of purpose-built websites. Today's web-agent expense is

Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models

arXiv:2605.17672v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance by generating long chains of thought (CoT), but often overthink, continuing to reason after a s

safetyarxiv-cs-cl

Support-Safe Variational Hybrid Filtering for Contact-Mode and Sparse-Law Recovery

arXiv:2605.16398v1 Announce Type: cross Abstract: Contact-rich robot dynamics are hybrid: a single observation can match several latent states and contact regimes (free, impact, stick--slip). A standa

Surface-Form Neural Sparse Retrieval: Robust Fuzzy Matching for Industrial Music Search

arXiv:2605.17762v1 Announce Type: new Abstract: Music search at the scale of Amazon Music presents a unique challenge: queries frequently deviate from indexed metadata due to misspellings, transpositi

tutorialsarxiv-cs-ai

SVL: Spike-based Vision-language Pretraining for Efficient 3D Open-world Understanding

arXiv:2505.17674v2 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. However, existing SNNs still exhibit a signif

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.17577v1 Announce Type: new Abstract: Large-scale pre-trained Vision-Language models (VLMs), such as CLIP, exhibit strong zero-shot generalization, yet remain highly vulnerable to impercepti

Tensor Channel Equivariant Graph Neural Networks for Molecular Polarizability Prediction

arXiv:2605.16891v1 Announce Type: new Abstract: We introduce a tensor-channel equivariant graph neural network for direct prediction of molecular polarizability tensors. Building on the efficient PaiN

The Silent Brush: Evaluating Artistic Style Leakage in AI Art Generation

arXiv:2605.17500v1 Announce Type: cross Abstract: Generative text-to-image models are typically trained on large-scale web-scraped datasets that include diverse visual content such as copyrighted and

tutorialsarxiv-cs-cv

Hardware

Token-Space Mask Prediction for Efficient Vision Transformer Segmentation

arXiv:2605.18177v1 Announce Type: new Abstract: Query-based Vision Transformer segmentation models typically reconstruct dense spatial feature maps to predict masks, inheriting design patterns from co

hardwarearxiv-cs-cv

Toward Near-Real-Time Marine Oil Spill Detection in SAR Imagery using Quantum-Assisted SVM

arXiv:2605.17217v1 Announce Type: cross Abstract: Marine oil spills require rapid detection to mitigate severe ecological and economic damage. While satellite-based Synthetic Aperture Radar (SAR) prov

researcharxiv-cs-lg

Towards Sustainable Growth: A Multi-Value-Aware Retrieval Framework for E-Commerce Search

arXiv:2605.17994v1 Announce Type: cross Abstract: New item growth is critical for maintaining a healthy ecosystem in large-scale e-commerce platforms. However, existing systems tend to prioritize pres

TPV: Parameter Perturbations Through the Lens of Test Prediction Variance

arXiv:2512.11089v4 Announce Type: replace-cross Abstract: We introduce test prediction variance (TPV)--the first-order sensitivity of a trained model's outputs to parameter perturbations--as a unifyin