Search: “models”

AAC: Admissible-by-Architecture Differentiable Landmark Compression for ALT

arXiv:2604.20744v1 Announce Type: new Abstract: We introduce extbf{AAC} (Architecturally Admissible Compressor), a differentiable landmark-selection module for ALT (A*, Landmarks, and Triangle inequal

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Research

ALAS: Adaptive Long-Horizon Action Synthesis via Async-pathway Stream Disentanglement

DGX agent

arXiv:2604.20721v1 Announce Type: new Abstract: Long-Horizon (LH) tasks in Human-Scene Interaction (HSI) are complex multi-step tasks that require continuous planning, sequential decision-making, and

researcharxiv-cs-ro

23 Apr 2026

All Languages Matter: Understanding and Mitigating Language Bias in Multilingual RAG

arXiv:2604.20199v1 Announce Type: new Abstract: Multilingual Retrieval-Augmented Generation (mRAG) leverages cross-lingual evidence to ground Large Language Models (LLMs) in global knowledge. However,

safetyarxiv-cs-cl

Ask Only When Needed: Proactive Retrieval from Memory and Skills for Experience-Driven Lifelong Agents

arXiv:2604.20572v1 Announce Type: new Abstract: Online lifelong learning enables agents to accumulate experience across interactions and continually improve on long-horizon tasks. However, existing me

safetyarxiv-cs-cl

Auto-Unrolled Proximal Gradient Descent: An AutoML Approach to Interpretable Waveform Optimization

arXiv:2603.17478v2 Announce Type: replace-cross Abstract: This study explores the combination of automated machine learning (AutoML) with model-based deep unfolding (DU) for optimizing wireless beamfo

researcharxiv-cs-ai

Benefits of Low-Cost Bio-Inspiration in the Age of Overparametrization

arXiv:2604.20365v1 Announce Type: cross Abstract: While Central Pattern Generators (CPGs) and Multi-Layer Perceptrons (MLP) are widely used paradigms in robot control, few systematic studies have been

Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformation

arXiv:2510.11423v3 Announce Type: replace-cross Abstract: Community Notes, the crowd-sourced misinformation governance system on X (formerly Twitter), allows users to flag misleading posts, attach con

Calibrating conditional risk

arXiv:2604.20409v1 Announce Type: new Abstract: We introduce and study the problem of calibrating conditional risk, which involves estimating the expected loss of a prediction model conditional on inp

researcharxiv-cs-lg

ChipCraftBrain: Validation-First RTL Generation via Multi-Agent Orchestration

arXiv:2604.19856v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise for generating Register-Transfer Level (RTL) code from natural language specifications, but single-shot gene

safetyarxiv-cs-ai

CLIP-RD: Relative Distillation for Efficient CLIP Knowledge Distillation

arXiv:2603.25383v3 Announce Type: replace Abstract: CLIP aligns image and text embeddings via contrastive learning and demonstrates strong zero-shot generalization. Its large-scale architecture requir

safetyarxiv-cs-cv

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment

arXiv:2510.18471v2 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) excel at code generation by learning from vast code corpora, a fundamental semantic gap remains between the

safetyarxiv-cs-ai

Computing the Reachability Value of Posterior-Deterministic POMDPs

arXiv:2602.07473v2 Announce Type: replace Abstract: Partially observable Markov decision processes (POMDPs) are a fundamental model for sequential decision-making under uncertainty. However, many veri

researcharxiv-cs-ai

Applications

DISCA: A Digital In-memory Stochastic Computing Architecture Using A Compressed Bent-Pyramid Format

arXiv:2511.17265v2 Announce Type: replace-cross Abstract: Nowadays, we are witnessing an Artificial Intelligence revolution that dominates the technology landscape in various application domains, such

applicationsarxiv-cs-ai

Distributional Inverse Reinforcement Learning

arXiv:2510.03013v3 Announce Type: replace Abstract: We propose a distributional framework for offline Inverse Reinforcement Learning (IRL) that jointly models uncertainty over reward functions and ful

safetyarxiv-cs-lg

Duluth at SemEval-2026 Task 6: DeBERTa with LLM-Augmented Data for Unmasking Political Question Evasions

arXiv:2604.20168v1 Announce Type: new Abstract: This paper presents the Duluth approach to SemEval-2026 Task 6 on CLARITY: Unmasking Political Question Evasions. We address Task 1 (clarity-level class

Effects of Cross-lingual Evidence in Multilingual Medical Question Answering

arXiv:2604.20531v1 Announce Type: new Abstract: This paper investigates Multilingual Medical Question Answering across high-resource (English, Spanish, French, Italian) and low-resource (Basque, Kazak

researcharxiv-cs-cl

Evaluating Black-Box Vulnerabilities with Wasserstein-Constrained Data Perturbations

arXiv:2603.15867v2 Announce Type: replace Abstract: The growing use of Machine Learning (ML) tools comes with critical challenges, such as limited model explainability. We propose a global explainabil

safetyarxiv-cs-lg

Local Ai

FA-Seg: A Fast and Accurate Diffusion-Based Method for Open-Vocabulary Segmentation

arXiv:2506.23323v5 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment objects from arbitrary text categories without requiring densely annotated datasets. Al

local-aiarxiv-cs-cv

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health

model-releasesarxiv-cs-lg

arXiv:2604.20735v1 Announce Type: new Abstract: Accurate condition monitoring of industrial equipment requires inferring latent degradation parameters from indirect sensor measurements under uncertain

Finding Duplicates in 1.1M BDD Steps: cukereuse, a Paraphrase-Robust Static Detector for Cucumber and Gherkin

arXiv:2604.20462v1 Announce Type: cross Abstract: Behaviour-Driven Development (BDD) suites accumulate step-text duplication whose maintenance cost is established in prior work. Existing detection tec

Agents

Forage V2: Knowledge Evolution and Transfer in Autonomous Agent Organizations

arXiv:2604.19837v1 Announce Type: new Abstract: Autonomous agents operating in open-world tasks -- where the completion boundary is not given in advance -- face denominator blindness: they systematica

agentsarxiv-cs-ai

From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents

arXiv:2604.20006v1 Announce Type: new Abstract: Personalized agents that interact with users over long periods must maintain persistent memory across sessions and update it as circumstances change. Ho

Gauge-covariant stochastic neural fields: Stability and finite-width effects

arXiv:2508.18948v2 Announce Type: replace-cross Abstract: We develop a gauge-covariant stochastic effective field theory for stability and finite-width effects in deep neural systems. The model uses c

researcharxiv-cs-lg

Global Offshore Wind Infrastructure: Deployment and Operational Dynamics from Dense Sentinel-1 Time Series

model-releasesarxiv-cs-cv

arXiv:2604.20822v1 Announce Type: new Abstract: The offshore wind energy sector is expanding rapidly, increasing the need for independent, high-temporal-resolution monitoring of infrastructure deploym

Hybrid Latent Reasoning with Decoupled Policy Optimization

arXiv:2604.20328v1 Announce Type: new Abstract: Chain-of-Thought (CoT) reasoning significantly elevates the complex problem-solving capabilities of multimodal large language models (MLLMs). However, a

safetyarxiv-cs-cv

Hybrid Multi-Phase Page Matching and Multi-Layer Diff Detection for Japanese Building Permit Document Review

arXiv:2604.19770v1 Announce Type: new Abstract: We present a hybrid multi-phase page matching algorithm for automated comparison of Japanese building permit document sets. Building permit review in Ja

Agents

If you're waiting for a sign... that might not be it! Mitigating Trust Boundary Confusion from Visual Injections on Vision-Language Agentic Systems

arXiv:2604.19844v1 Announce Type: cross Abstract: Recent advances in embodied Vision-Language Agentic Systems (VLAS), powered by large vision-language models (LVLMs), enable AI systems to perceive and

agentsarxiv-cs-ai

IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory

arXiv:2604.20136v1 Announce Type: cross Abstract: Correcting errors in long-video understanding is disproportionately costly: existing multimodal pipelines produce opaque, end-to-end outputs that expo

Local Ai

Learning Spatial-Temporal Coherent Correlations for Speech-Preserving Facial Expression Manipulation

arXiv:2604.20226v1 Announce Type: new Abstract: Speech-preserving facial expression manipulation (SPFEM) aims to modify facial emotions while meticulously maintaining the mouth animation associated wi

local-aiarxiv-cs-cv

Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication

arXiv:2604.19895v1 Announce Type: new Abstract: A well-known limitation of AI systems is presumptuousness: the tendency of AI systems to provide confident answers when information may be lacking. This

Less Languages, Less Tokens: An Efficient Unified Logic Cross-lingual Chain-of-Thought Reasoning Framework

arXiv:2604.20090v1 Announce Type: new Abstract: Cross-lingual chain-of-thought (XCoT) with self-consistency markedly enhances multilingual reasoning, yet existing methods remain costly due to extensiv

LEXIS: LatEnt ProXimal Interaction Signatures for 3D HOI from an Image

arXiv:2604.20800v1 Announce Type: new Abstract: Reconstructing 3D Human-Object Interaction from an RGB image is essential for perceptive systems. Yet, this remains challenging as it requires capturing

Agents

LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals

arXiv:2411.10109v2 Announce Type: replace Abstract: Machine learning can predict human behavior well when substantial structured data and well-defined outcomes are available, but these models are typi

agentsarxiv-cs-ai

LLM Agents Predict Social Media Reactions but Do Not Outperform Text Classifiers: Benchmarking Simulation Accuracy Using 120K+ Personas of 1511 Humans

arXiv:2604.19787v1 Announce Type: cross Abstract: Social media platforms mediate how billions form opinions and engage with public discourse. As autonomous AI agents increasingly participate in these

safetyarxiv-cs-ai

MAPRPose: Mask-Aware Proposal and Amodal Refinement for Multi-Object 6D Pose Estimation

model-releasesarxiv-cs-cv

arXiv:2604.20650v1 Announce Type: new Abstract: 6D object pose estimation in cluttered scenes remains challenging due to severe occlusion and sensor noise. We propose MAPRPose, a two-stage framework t

MetaboNet: The Largest Publicly Available Consolidated Dataset for Type 1 Diabetes Management

arXiv:2601.11505v2 Announce Type: replace-cross Abstract: Progress in Type 1 Diabetes (T1D) algorithm development is limited by the fragmentation and lack of standardization across existing T1D manage

MGDA-Decoupled: Geometry-Aware Multi-Objective Optimisation for DPO-based LLM Alignment

arXiv:2604.20685v1 Announce Type: new Abstract: Aligning large language models (LLMs) to desirable human values requires balancing multiple, potentially conflicting objectives such as helpfulness, tru

safetyarxiv-cs-lg

Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL

model-releasesarxiv-cs-lg

arXiv:2506.20904v2 Announce Type: replace Abstract: We study offline reinforcement learning in average-reward MDPs, which presents increased challenges from the perspectives of distribution shift and

Optimizing User Profiles via Contextual Bandits for Retrieval-Augmented LLM Personalization

arXiv:2601.12078v2 Announce Type: replace Abstract: Large language models (LLMs) excel at general-purpose tasks, yet adapting their responses to individual users remains challenging. Retrieval augment

researcharxiv-cs-cl

Over-Refusal and Representation Subspaces: A Mechanistic Analysis of Task-Conditioned Refusal in Aligned LLMs

arXiv:2603.27518v2 Announce Type: replace Abstract: Aligned language models that are trained to refuse harmful requests also exhibit over-refusal: they decline safe instructions that seemingly resembl

researcharxiv-cs-cl

OVPD: A Virtual-Physical Fusion Testing Dataset of OnSite Auton-omous Driving Challenge

model-releasesarxiv-cs-ro

arXiv:2604.20423v1 Announce Type: new Abstract: The rapid iteration of autonomous driving algorithms has created a growing demand for high-fidelity, replayable, and diagnosable testing data. However,

Pairing Regularization for Mitigating Many-to-One Collapse in GANs

arXiv:2604.20130v1 Announce Type: cross Abstract: Mode collapse remains a fundamental challenge in training generative adversarial networks (GANs). While existing works have primarily focused on inter

Personalized electric vehicle energy consumption estimation framework that integrates driver behavior with map data

arXiv:2604.20764v1 Announce Type: cross Abstract: This paper presents a personalized Battery Electric Vehicle (BEV) energy consumption estimation framework that integrates map-based contextual feature

researcharxiv-cs-lg

Physics-Informed Conditional Diffusion for Motion-Robust Retinal Temporal Laser Speckle Contrast Imaging

arXiv:2604.20594v1 Announce Type: new Abstract: Retinal laser speckle contrast imaging (LSCI) is a noninvasive optical modality for monitoring retinal blood flow dynamics. However, conventional tempor

Prism: An Evolutionary Memory Substrate for Multi-Agent Open-Ended Discovery

arXiv:2604.19795v1 Announce Type: new Abstract: We introduce prism{} (extbf{P}robabilistic extbf{R}etrieval with extbf{I}nformation-extbf{S}tratified extbf{M}emory), an evolutionary memory substrate f

Random Walk on Point Clouds for Feature Detection

arXiv:2604.20474v1 Announce Type: new Abstract: The points on the point clouds that can entirely outline the shape of the model are of critical importance, as they serve as the foundation for numerous

RefAerial: A Benchmark and Approach for Referring Detection in Aerial Images

model-releasesarxiv-cs-cv

arXiv:2604.20543v1 Announce Type: new Abstract: Referring detection refers to locate the target referred by natural languages, which has recently attracted growing research interests. However, existin

Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference

model-releasesarxiv-cs-lg

arXiv:2604.20775v1 Announce Type: new Abstract: Trajectory Inference (TI) seeks to recover latent dynamical processes from snapshot data, where only independent samples from time-indexed marginals are