Search: “evaluation”

arXiv:2602.23234v4 Announce Type: replace-cross Abstract: Large-scale commercial search systems optimize for relevance to drive successful sessions that help users find what they are looking for. To m

applicationsarxiv-cs-ai

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Research

ScaRF-SLAM: Scale-Consistent Reconstruction with Feed-Forward Models and Classical Visual SLAM

DGX agent

arXiv:2606.00307v1 Announce Type: new Abstract: Recent works have explored unifying SLAM with geometric foundation models (GFMs). However, directly using GFM predictions for tracking is highly sensiti

researcharxiv-cs-ro

2 Jun 2026

Tutorials

SCL: Towards Domain Generalization via Single-Temporal Multimodal Contrastive Learning for Remote Sensing Change Detection

arXiv:2404.11326v5 Announce Type: replace Abstract: In recent years, change detection and anomaly detection models based on CNN and transformer have achieved remarkable success across various datasets

tutorialsarxiv-cs-cv

Score-Control for Hallucination Reduction in Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2606.00377v1 Announce Type: new Abstract: Diffusion models have emerged as the backbone of modern generative AI, powering advances in vision, language, audio and other modalities. Despite their

Score imes Decoder: A Unified View of Unsupervised Inference-Time Scaling for Hallucination Mitigation

arXiv:2606.00739v1 Announce Type: new Abstract: Large language models hallucinate even when the answer lies within their parameters. While inference-time scaling can surface this latent knowledge, the

researcharxiv-cs-lg

Local Ai

Segment-driven Structural Induction and Semantic Alignment for Heterogeneous Tabular Representation

arXiv:2606.01890v1 Announce Type: new Abstract: Real-world domains often contain heterogeneous tables whose headers vary while their underlying attribute semantics are shared, making it difficult to i

local-aiarxiv-cs-lg

Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems

arXiv:2606.01416v1 Announce Type: new Abstract: Tool-augmented large language model (LLM) agents rely on orchestration layers that coordinate planning, retrieval, tool invocation, validation, memory,

Self-Imitated Diffusion Policy for Efficient and Robust Visual Navigation

model-releasesarxiv-cs-ro

arXiv:2601.22965v2 Announce Type: replace Abstract: Diffusion policies (DP) have demonstrated significant potential in visual navigation by capturing diverse multi-modal trajectory distributions. Howe

Self-supervised Monocular Depth and Pose Estimation for Endoscopy with Latent Priors

arXiv:2411.17790v3 Announce Type: replace-cross Abstract: Accurate 3D mapping in endoscopy enables quantitative, holistic lesion characterization within the gastrointestinal (GI) tract, requiring reli

SentimentLens: Reconciling Sentiment and Ratings via Dual-Modality in the Hospitality Sector

arXiv:2606.00084v1 Announce Type: cross Abstract: Online travel platforms generate vast volumes of user-generated hotel reviews, offering rich opportunities to understand traveler experiences at scale

Shape-Prior-Based Point Cloud Completion for Single-Stage Fully Sparse 3D Object Detection

arXiv:2606.00688v1 Announce Type: new Abstract: Single-stage fully sparse 3D object detectors rely on point clouds data to detect objects in autonomous driving scenarios. However, the sparsity and inc

safetyarxiv-cs-cv

Shape Your Body: Value Gradients for Multi-Embodiment Robot Design

arXiv:2606.00702v1 Announce Type: cross Abstract: We propose to turn generalist multi-embodiment value functions into reusable models for robot design. Instead of running a new reinforcement learning

ShapeLib: Designing a library of programmatic 3D shape abstractions with Large Language Models

arXiv:2502.08884v3 Announce Type: replace-cross Abstract: We present ShapeLib, the first method that uses the priors of Large Language Models (LLMs) to design libraries of programmatic 3D shape abstra

Applications

ShelfAware: Real-Time Semantic Localization in Quasi-Static Environments with Low-Cost Sensors

arXiv:2512.09065v2 Announce Type: replace-cross Abstract: Many indoor workspaces are quasi-static: their global geometric layout is stable, but local semantics change continually, producing repetitive

applicationsarxiv-cs-ai

SHERLOCK: Towards Dynamic Knowledge Adaptation in LLM-enhanced E-commerce Risk Management

arXiv:2510.08948v4 Announce Type: replace-cross Abstract: Effective e-commerce risk management requires in-depth case investigations to identify emerging fraud patterns in highly adversarial environme

SilentDrift: Exploiting Action Chunking for Stealthy Backdoor Attacks on Vision-Language-Action Models

arXiv:2601.14323v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are increasingly deployed in safety-critical robotic applications, yet their security vulnerabilities rema

Simulating Macroeconomic Expectations in Survey Experiments with LLM-based Economic Agents

arXiv:2505.17648v5 Announce Type: replace-cross Abstract: We introduce a framework for simulating macroeconomic expectations in survey experiments using LLM-based economic agents (LLM Agents). We cons

SindBERT, the Sailor: Charting the Seas of Turkish NLP

model-releasesarxiv-cs-cl

arXiv:2510.21364v2 Announce Type: replace Abstract: Transformer models have revolutionized NLP, yet many morphologically rich languages remain underrepresented in large-scale pre-training efforts. Wit

SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories

arXiv:2606.01311v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on reusable external skills to solve long-horizon interactive tasks. Existing training-free skill

SkillRevise: Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision

arXiv:2606.01139v1 Announce Type: new Abstract: Agent skills are procedural artifacts that enable LLM agents to execute workflows, verify constraints, and recover from failures. Existing self-evolving

SkillSmith: Co-Evolving Skills and Tools for Self-Improving Agent Systems

arXiv:2606.01314v1 Announce Type: new Abstract: Recent self-evolving agents have shown that skills can be discovered, refined, and accumulated through execution. However, existing skill-evolution fram

SkyShield: Occupancy as a Safety Interface for Low-Altitude UAV Autonomy

arXiv:2606.00747v1 Announce Type: cross Abstract: For low-altitude Unmanned Aerial Vehicle (UAV) autonomy, 3D spatial understanding is not merely a perception objective, but the safety interface betwe

SortingHat: Redefining Operating Systems Education with a Tailored Digital Teaching Assistant

arXiv:2606.00015v1 Announce Type: cross Abstract: Operating Systems (OS) courses are among the most challenging in computer science education due to the complexity of internal structures and the diver

Spatiotemporal Multi-Task Graph Transformer for Trip-Level Transit Prediction

arXiv:2606.00572v1 Announce Type: new Abstract: Passenger count data from public transit systems reveals urban mobility patterns and is essential for planning, operation, and optimisation. However, no

safetyarxiv-cs-lg

Spectra-Guided Neural Tucker Factorization

model-releasesarxiv-cs-lg

arXiv:2606.00584v1 Announce Type: cross Abstract: This paper proposes Spectra-Guided Neural Tucker Factorization (SG-NTF) for High-Dimensional and Incomplete (HDI) tensor completion. Circumventing dis

STEM: Semantic Target Search and Exploration using MAVs in Cluttered Environments

arXiv:2606.00762v1 Announce Type: new Abstract: Autonomous target search is crucial for deploying Micro Aerial Vehicles (MAVs) in emergency response and rescue missions. Existing approaches either foc

agentsarxiv-cs-ro

StreamingVLM: Real-Time Understanding for Infinite Video Streams

arXiv:2510.09608v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) could power real-time assistants and autonomous agents, but they face a critical challenge: understanding near-i

Applications

Structure-Aware Consistency Priors for Shape from Polarization in Complex Media

arXiv:2606.00509v1 Announce Type: new Abstract: Recovering surface normals from single view polarization images in complex media remains challenging. This paper focuses on ice as a representative comp

applicationsarxiv-cs-cv

Structured Visual Evidence Decomposition for Evidence-Grounded Multimodal Screening of Obstructive Sleep Apnea-Hypopnea Syndrome

arXiv:2606.00087v1 Announce Type: cross Abstract: Effective pre-polysomnography screening for obstructive sleep apnea-hypopnea syndrome (OSAHS) requires combining clinical risk factors with visible cr

SuperMemory-VQA: An Egocentric Visual Question-Answering Benchmark for Long-Horizon Memory

model-releasesarxiv-cs-cv

arXiv:2606.00825v1 Announce Type: new Abstract: AI glasses present a compelling platform for AI agents to serve as personalized memory assistants. To be genuinely useful, such systems must move beyond

SurrogateSHAP: Training-Free Contributor Attribution for Text-to-Image (T2I) Models

arXiv:2601.22276v2 Announce Type: replace-cross Abstract: As Text-to-Image (T2I) diffusion models are increasingly used in real-world creative workflows, a principled framework for valuing contributor

safetyarxiv-cs-cv

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design

arXiv:2510.23379v2 Announce Type: replace-cross Abstract: We investigate a relatively under-explored class of hybrid neurosymbolic models that integrate symbolic learning with neural reasoning to cons

Symmetric Hermite quadrature-based balanced truncation for learning linear dynamical systems from derivative data

arXiv:2606.00298v1 Announce Type: cross Abstract: Data-driven reduced-order modeling is an essential component in the computer-aided design of control systems. In this work, we present a novel symmetr

researcharxiv-cs-lg

Tutorials

Tackling the Root of Misinformation by Teaching Laypeople about Logical Fallacies via Socratic Questioning and Critical Argumentation

arXiv:2606.01020v1 Announce Type: new Abstract: Identifying logical fallacies in everyday discourse is challenging for many people. This challenge is amplified in the era of Large Language Models (LLM

tutorialsarxiv-cs-ai

TalkTag: Fine-Grained Morphosyntactic Error Annotation for Transcribed Speech

arXiv:2606.01820v1 Announce Type: new Abstract: Fine-grained morphosyntactic error annotation is important in clinical and developmental language research, yet it is labour-intensive, expert-dependent

researcharxiv-cs-cl

Task diversity produces systematic transfer but inhibits continual reinforcement learning

arXiv:2606.00880v1 Announce Type: cross Abstract: Continual reinforcement learning aims to produce agents that learn not only to improve at their current tasks but also to adapt as task distributions

TCAR-Gen: Temporal Graph Retrieval with Evidence Fusion for Knowledge-Grounded Generation

arXiv:2606.00029v1 Announce Type: cross Abstract: Retrieval-augmented generation systems struggle with temporal reasoning and evidence fusion when answering complex questions over historical criminal

The Refusal--Compliance Tradeoff: A Large-Scale Safety Behavior Audit of Large Language Models

arXiv:2605.05427v2 Announce Type: replace Abstract: Refusal rates are a poor proxy for LLM safety, i.e., a model may over-refuse benign prompts while still complying with harmful ones. We audit both f

The Representation-Rationalizability Tradeoff in Reward Learning

arXiv:2606.00291v1 Announce Type: cross Abstract: In RLHF, each training example contains a prompt x and two candidate responses y,y', and annotators provide pairwise preferences between these respons

researcharxiv-cs-lg

The Role of Ambiguity in Error Prediction via Uncertainty Quantification

arXiv:2606.02093v1 Announce Type: cross Abstract: The task of Error Prediction, namely predicting whether a model output is correct, is commonly tackled with Uncertainty Quantification (UQ). However,

Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models

arXiv:2606.02580v1 Announce Type: new Abstract: Inverse graphics is a longstanding and highly underconstrained problem that seeks to reconstruct images as editable 3D scenes which can be rendered, rel

agentsarxiv-cs-cv

ThinkSwitch: Context Distillation with LoRA and Weight Interpolation for Specific-Purpose Reasoning Tasks

arXiv:2606.01080v1 Announce Type: cross Abstract: Large language models often improve on difficult tasks by spending inference-time compute on a reasoning trace before producing the final answer. That

Threading Optimization for Vision-Language-Action Model Inference in Low-Cost Smart Agricultural Manipulation

arXiv:2606.00966v1 Announce Type: new Abstract: Vision-Language Action (VLA) models continue to face challenges such as slow inference speed and difficulty performing fine-grained motion adjustments,

safetyarxiv-cs-ro

Tiny Recursive Models for Solving the J2-Perturbed Lambert Problem

model-releasesarxiv-cs-lg

arXiv:2606.00895v1 Announce Type: cross Abstract: This paper presents a fast, recursive neural solver for the J2-perturbed Lambert problem based on Tiny Recursive Models (TRM), termed the TRM-Perturbe

Toward accurate RUL and SoH estimation using reinforced graph-based physics-informed neural networks enhanced with dynamic weights

arXiv:2507.09766v2 Announce Type: replace-cross Abstract: Accurate estimation of Remaining Useful Life (RUL) and State of Health (SoH) is essential for reliable Prognostics and Health Management (PHM)

Towards a General Intelligence and Interface for Wearable Health Data

arXiv:2605.22759v2 Announce Type: replace Abstract: While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personal

Towards Anytime Retrieval: A Benchmark for Anytime Person Re-Identification

model-releasesarxiv-cs-cv

arXiv:2509.16635v2 Announce Type: replace Abstract: In real applications, person re-identification (ReID) is expected to retrieve the target person at any time, including both daytime and nighttime, r

Tutorials

Towards Automated Discovery: A Review of Generative Models, Multimodal Learning and Closed-Loop Workflows in Inverse Materials Design

arXiv:2606.02507v1 Announce Type: cross Abstract: Inverse materials design is shifting materials discovery from forward prediction to targeted proposal of candidates that satisfy objectives under phys

tutorialsarxiv-cs-lg