Search: “evaluation”

MOAR Planner: Multi-Objective and Adaptive Risk-Aware Path Planning for Infrastructure Inspection with a UAV

arXiv:2606.30575v1 Announce Type: new Abstract: The problem of autonomous navigation for UAV inspection remains challenging as it requires effectively navigating in close proximity to obstacles, while

safetyarxiv-cs-ro

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Research

Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders

DGX agent

arXiv:2507.23220v2 Announce Type: replace Abstract: Traditional topic models are effective at uncovering latent themes in large text collections. However, due to their reliance on bag-of-words represe

researcharxiv-cs-cl

30 Jun 2026

Modelling Human Values for Value-Aware Multi-Agent Systems

arXiv:2402.06359v2 Announce Type: replace Abstract: One of today's most pressing societal challenges is building AI systems whose behaviour, or the behaviour it enables within communities of interacti

safetyarxiv-cs-ai

Momentum Guidance: Plug-and-Play Guidance for Flow Models

arXiv:2602.20360v2 Announce Type: replace-cross Abstract: Flow-based generative methods offer a simple and effective framework for high-fidelity generation, yet pretrained flow models are rarely used

researcharxiv-cs-cv

MotionAtlas: Detailed Region Captioning for Motion-Centric Videos

arXiv:2606.29531v1 Announce Type: cross Abstract: We propose MotionAtlas, a system for detailed captioning of motion-centric videos, comprising (1) a dedicated human-annotated benchmark, (2) a scalabl

Multimodal Graph RAG for Long-range Visually Rich Document Understanding

arXiv:2606.28780v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are widely applied to visual document understanding. However, comprehending long documents remains an issue b

MuseBench: Benchmarking Intent-Level Audiovisual Arts Understanding in MLLMs

arXiv:2606.30026v1 Announce Type: cross Abstract: Audiovisual arts encompass diverse creative disciplines, including cinema, visual arts, stage performance, and game design, where artistic meaning ari

Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models

arXiv:2603.18907v2 Announce Type: replace Abstract: We propose a new Neural Galerkin Normalizing Flow framework to approximate the transition probability density function of a diffusion process by sol

researcharxiv-cs-lg

OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale

arXiv:2407.19633v4 Announce Type: replace Abstract: Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare. However, most such problems are still solved heuri

Phonological Perception of Sign Language Models

arXiv:2606.28667v1 Announce Type: new Abstract: Sign languages are compositional systems where meaning arises by combining sublexical phonological parameters, such as handshape, location, and movement

safetyarxiv-cs-cl

Pointer-CAD v2: Plan-Then-Construct CAD Generation with Dimension-Aware Parametric Precision

arXiv:2606.29301v1 Announce Type: new Abstract: Computer-aided design (CAD) plays a fundamental role in modern manufacturing by providing the high precision required for industrial production. Recent

Post-training for Efficient Communication via Convention Formation

arXiv:2508.06482v2 Announce Type: replace-cross Abstract: Humans communicate with increasing efficiency in multi-turn interactions, by adapting their language and forming ad-hoc conventions. In contra

Primary ICD Category Prediction using LLM-based Probing

arXiv:2606.28798v1 Announce Type: new Abstract: Objective: ICD codes are central to reimbursement, research, and population health surveillance, yet automated coding systems often struggle to integrat

RA-QA: A Benchmarking System for Respiratory Audio Question Answering Under Real-World Heterogeneity

model-releasesarxiv-cs-lg

arXiv:2602.18452v3 Announce Type: replace-cross Abstract: As conversational multimodal AI tools are increasingly adopted to process patient data for health assessment, robust benchmarks are needed to

REPAIR-Bench: A Benchmark for Robot Error Perception And Interaction Recovery

model-releasesarxiv-cs-ro

arXiv:2606.29937v1 Announce Type: new Abstract: Understanding how users perceive and respond to robot failures is essential for building robust and trustworthy robot systems. Prior work, however, (i)

Resolution Thresholds in VLM Detection of Harmful ASCII Art Across Construction Modes and Languages

arXiv:2606.29649v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) are increasingly deployed as content moderation tools, yet they remain vulnerable to jailbreak attacks in which harm

safetyarxiv-cs-cl

Reward-Free Code Alignment from Pretrained or Fine-Tuned LLM: Unpacking the Trade-offs for Code Generation

arXiv:2606.28998v1 Announce Type: cross Abstract: Large Language Model (LLM) alignment trains an LLM using preference data to produce outputs that better meet established quality standards. While LLM

SADL: What to Ignore? A Benchmark for Subject-Aware Distractor Localization

arXiv:2606.30393v1 Announce Type: new Abstract: Photographs frequently contain visual distractors besides foregrounds and backgrounds of the intended subject, competing for attention and weakening com

SciIR: A Large-scale Training Dataset and Benchmark for Scientific Image Reasoning Generation

arXiv:2606.30124v1 Announce Type: new Abstract: While Text-to-Image (T2I) models have shown remarkable success in generating photorealistic visual content, they still struggle with the rigorous semant

Applications

Solver-Verified Formulation Generation and Selection for Multi-Warehouse Inventory Allocation Using Large Language Models

arXiv:2606.29366v1 Announce Type: cross Abstract: Balance-oriented multi-warehouse inventory allocation is a recurring decision problem in large-scale e-commerce supply chains, in which a fixed replen

applicationsarxiv-cs-ai

Staged Hybridisation for Visual Quantum Reinforcement Learning via Knowledge Distillation

arXiv:2606.30520v1 Announce Type: cross Abstract: Visual environments are a demanding setting for quantum reinforcement learning (QRL): high-dimensional observations, unstable RL optimisation, and con

safetyarxiv-cs-lg

StrucTab: A Structured Optimization Framework for Table Parsing

arXiv:2606.29905v1 Announce Type: new Abstract: Table parsing aims to convert table images into structured, machine-readable representations, a task requiring the joint perception of complex spatial l

SVCBench: A Streaming Video Counting Benchmark for Spatial-Temporal State Maintenance

arXiv:2603.12703v3 Announce Type: replace Abstract: Video understanding requires models to continuously track and update world state during playback. Although existing benchmarks have advanced video u

SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scenarios

arXiv:2511.17649v4 Announce Type: replace-cross Abstract: Tangible control interfaces (TCIs), such as appliance panels, remotes, elevators, and embedded GUIs, are a fundamental component of everyday h

TACO: A Test and Check Framework for Robust Pose Graph Optimization

arXiv:2606.29851v1 Announce Type: new Abstract: Pose Graph Optimization (PGO) is one of the most widely adopted approaches for solving Simultaneous Localization and Mapping (SLAM) problems. However, P

researcharxiv-cs-ro

Tutorials

Temporal Feature Extractors in EEG Foundation Models: A Controlled Comparison Including a Pretrained Time-Series Model

arXiv:2606.30104v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models aim to learn generalizable representations from large-scale brain recordings. However, the role of tempor

tutorialsarxiv-cs-ai

The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning

arXiv:2606.28843v1 Announce Type: cross Abstract: Fine-tuning a large language model is a ubiquitous method for enhancing its capability on a specific downstream task. However, prior work has shown th

Towards Continual Motion-Language Agents: LoRA Variants for Incremental Motion Understanding and Generation

arXiv:2606.30266v1 Announce Type: cross Abstract: Motion-language agents must possess the bidirectional capability to both understand human movement (motion-to-text, M2T) and generate it from natural

Transformer-Based Active Learning for Data-Efficient Vaccine Epitope Selection in PRRS

arXiv:2606.28659v1 Announce Type: cross Abstract: High-fidelity molecular docking simulations can produce biologically relevant estimates of epitope-receptor binding affinity but are computationally e

safetyarxiv-cs-lg

Translating Natural Language to Strategic Temporal Specifications via LLMs

arXiv:2606.30441v1 Announce Type: cross Abstract: A rigorous formalization of system requirements is a fundamental prerequisite for the verification of Multi-Agent Systems (MAS). However, writing corr

Value-Action Alignment in Large Language Models under Privacy-Prosocial Conflict

arXiv:2601.03546v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to simulate decision-making tasks involving personal data sharing, where privacy concerns a

safetyarxiv-cs-ai

VIGIL: Part-Grounded Structured Reasoning for Generalizable Deepfake Detection

arXiv:2603.21526v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) offer a promising path toward interpretable deepfake detection by generating textual explanations. However,

Vision-Language Models for Deployable Social Robot Navigation: Bridging Semantic Reasoning and Low-Level Control

arXiv:2606.28760v1 Announce Type: new Abstract: Social robot navigation (SRN) requires more than geometric path planning; it demands understanding human intentions, social norms, and contextual cues t

safetyarxiv-cs-ro

When May I Help You? On The Effect of Proactivity on Group Human-Robot Collaboration

arXiv:2606.28469v1 Announce Type: new Abstract: Robot initiative is a central challenge in multi-party human-robot collaboration. A robot that contributes without being addressed may provide timely su

researcharxiv-cs-ro

Which Tokens Need Context? A Reference-Based Analysis of Translation Responsibility Using Fertility and Entropy

arXiv:2606.29489v1 Announce Type: new Abstract: When humans translate, not every word depends equally on the surrounding context. Some tokens, particularly function words like pronouns and auxiliaries

researcharxiv-cs-cl

Tutorials

Who Plays Which Role When? Communication Role Dynamics for Peer Recognition and Team Performance Prediction

arXiv:2606.28544v1 Announce Type: cross Abstract: Team roles offer an interpretable lens on collaboration, yet computational studies of roles often rely on domain-specific personas or data-driven clus

tutorialsarxiv-cs-cl

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection

arXiv:2606.30587v1 Announce Type: cross Abstract: Researchers and practitioners increasingly apply Large Language Models (LLMs) for automated vulnerability detection. Recent work has shown that LLMs a

safetyarxiv-cs-ai

XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generation

arXiv:2412.15529v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) synergizes the retrieval of pertinent data with the generative capabilities of Large Language Models (LLM

Zero-Label Driving Scenario Complexity Detection via Joint Embedding Predictive Architecture

arXiv:2606.28383v1 Announce Type: new Abstract: Identifying complex and safety-critical driving scenarios in large unlabelled datasets is an important but expensive problem. Existing approaches rely o

safetyarxiv-cs-cv

Agentic Hardware Design as Repository-Level Code Evolution

arXiv:2606.28279v1 Announce Type: cross Abstract: We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled int

An Approach to Enriching Surgical Video Datasets for Fine-Grained Spatial-Temporal Understanding of Vision-Language Models

arXiv:2604.00784v2 Announce Type: replace Abstract: Surgical video understanding is a crucial prerequisite for advancing Computer-Assisted Surgery. While vision-language models (VLMs) have recently be

researcharxiv-cs-cv

An Empirical Analysis of Factual Errors in Human-Written Text and its Application

model-releasesarxiv-cs-cl

arXiv:2606.27959v1 Announce Type: new Abstract: Factual Error Detection (FED), which is the task of identifying factually incorrect spans in a given text, has long been recognized as an important rese

Benchmarking Multi-Modal Graph-based Social Media Popularity Prediction

arXiv:2606.27539v1 Announce Type: cross Abstract: Social media popularity prediction aims to forecast the future reach or influence of online content from early-stage observations. Accurate prediction

CalBrief: A Pilot Diagnostic Benchmark for Evidence-Calibrated Scientific Briefing with Large Language Models

arXiv:2606.27383v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as research assistants, yet it remains unclear whether they can calibrate research takeaways to the

CausalFlip: A Benchmark for LLM Causal Judgment Beyond Semantic Matching

arXiv:2602.20094v2 Announce Type: replace Abstract: As large language models (LLMs) witness increasing deployment in complex, high-stakes decision-making scenarios, it becomes imperative to ground the

Cloud CISO Perspectives: How Google Cloud Security uses AI internally

model-releasesgoogle-cloud-ai

Welcome to the second Cloud CISO Perspectives for June 2026. Today, we’re discussing how we use AI to chart a path to autonomous software development lifecycle security.As with all Cloud CISO Perspect

Applications

COCOLogic-V2: Identifying Logical Inconsistencies via Truly Hard-Negatives

arXiv:2606.28194v1 Announce Type: new Abstract: While interpretable models such as concept bottleneck models (CBMs) and program synthesis methods enable verification of model decisions, their evaluati

applicationsarxiv-cs-lg

Compression-Driven Anomaly Detection in Brain MRI Using an Interpretable Quantum Autoencoder

arXiv:2606.27411v1 Announce Type: cross Abstract: We study a quantum autoencoder (QAE) for compression-driven anomaly detection in brain MRI data. The approach leverages angle encoding to map image pa