Search: “evaluation”

Are Compact Rationales Free? Measuring Tile Selection Headroom in Frozen WSI-MIL

arXiv:2605.12575v1 Announce Type: cross Abstract: Whole-slide image (WSI) multiple instance learning (MIL) classifiers can achieve strong slide-level AUC while leaving the full-bag prediction opaque.

researcharxiv-cs-ai

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Automated alignment is harder than you think

DGX agent

arXiv:2605.06390v2 Announce Type: replace Abstract: A leading proposal for aligning artificial superintelligence (ASI) is to use AI agents to automate an increasing fraction of alignment research as c

safetyarxiv-cs-ai

14 May 2026

Benchmarking Attribute Discrimination in Infant-Scale Vision-Language Models

arXiv:2512.18951v3 Announce Type: replace Abstract: Infants learn not only object categories but also fine-grained visual attributes such as color, size, and texture from limited experience. Prior inf

Local Ai

BlockVLA: Accelerating Autoregressive VLA via Block Diffusion Finetuning

arXiv:2605.13382v1 Announce Type: new Abstract: While autoregressive (AR) Vision-Language-Action (VLA) models have demonstrated formidable reasoning capabilities in robotic tasks, their sequential dec

local-aiarxiv-cs-ro

Local Ai

CANTANTE: Optimizing Agentic Systems via Contrastive Credit Attribution

arXiv:2605.13295v1 Announce Type: cross Abstract: LLM-based multi-agent systems have demonstrated strong performance across complex real-world tasks, such as software engineering, predictive modeling,

local-aiarxiv-cs-ai

Children's English Reading Story Generation via Supervised Fine-Tuning of Compact LLMs with Controllable Difficulty and Safety

arXiv:2605.13709v1 Announce Type: cross Abstract: Large Language Models (LLMs) are widely applied in educational practices, such as for generating children's stories. However, the generated stories ar

Continual Learning with Multilingual Foundation Model

arXiv:2605.13415v1 Announce Type: cross Abstract: This paper presents a multi-stage framework for detecting reclaimed slurs in multilingual social media discourse. It addresses the challenge of identi

researcharxiv-cs-ai

Do Activation Verbalization Methods Convey Privileged Information?

arXiv:2509.13316v4 Announce Type: replace-cross Abstract: Recent interpretability methods have proposed to translate LLM internal representations into natural language descriptions using a second verb

DocAtlas: Multilingual Document Understanding Across 80+ Languages

arXiv:2605.12623v1 Announce Type: cross Abstract: Multilingual document understanding remains limited for low-resource languages due to scarce training data and model-based annotation pipelines that p

Domain Adaptation of Large Language Models for Polymer-Composite Additive Manufacturing Using Retrieval-Augmented Generation and Fine-Tuning

arXiv:2605.12516v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) often struggle to generate reliable responses in specialized engineering domains due to limited domain gr

Driving Intents Amplify Planning-Oriented Reinforcement Learning

arXiv:2605.12625v1 Announce Type: cross Abstract: Continuous-action policies trained on a single demonstrated trajectory per scene suffer from mode collapse: samples cluster around the demonstrated ma

safetyarxiv-cs-cv

Ego2World: Compiling Egocentric Cooking Videos into Executable Worlds for Belief-State Planning

arXiv:2605.13335v1 Announce Type: new Abstract: Embodied agents in household environments must plan under partial observation: they need to remember objects, track state changes, and recover when acti

Emotional Expression in Low-Degrees-of-Freedom Robots: Assessing Perception with Reachy Mini

model-releasesarxiv-cs-ro

arXiv:2605.12786v1 Announce Type: new Abstract: Emotion expression is central to human--robot interaction, yet little is known about how people interpret affect on robots with sparse, non-anthropomorp

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition

arXiv:2605.13193v1 Announce Type: new Abstract: Fine-grained recognition in everyday life is often not a closed-book classification problem: when encountering unfamiliar objects, humans actively searc

agentsarxiv-cs-cv

Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following

model-releasesarxiv-cs-ro

arXiv:2509.10796v4 Announce Type: replace Abstract: Robot person following (RPF) -- mobile robots that follow and assist a specific person -- has emerging applications in personal assistance, security

From Instance Selection to Fixed-Pool Data Recipe Search for Supervised Fine-Tuning

arXiv:2605.12944v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) data selection is commonly formulated as instance ranking: score each example and retain a top-k subset. However, effective

Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report

arXiv:2605.13555v1 Announce Type: cross Abstract: Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density

researcharxiv-cs-ai

Graph-Based Financial Fraud Detection with Calibrated Risk Scoring and Structural Regularization

arXiv:2605.12782v1 Announce Type: new Abstract: Financial transaction fraud prevention faces challenges such as complex relationship structures, concealed behavioral patterns, and dynamically changing

safetyarxiv-cs-lg

GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?

arXiv:2605.12827v1 Announce Type: cross Abstract: Graph neural networks (GNNs) deployed as cloud services can be stolen through model-extraction attacks, which train a surrogate from query responses t

Harnessing Agentic Evolution

arXiv:2605.13821v1 Announce Type: new Abstract: Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, e

agentsarxiv-cs-ai

ImageAttributionBench: How Far Are We from Generalizable Attribution?

arXiv:2605.12967v1 Announce Type: new Abstract: The rapid advancement of generative AI has enabled the creation of highly realistic and diverse synthetic images, posing critical challenges for image p

IndicMedDialog: A Parallel Multi-Turn Medical Dialogue Dataset for Accessible Healthcare in Indic Languages

arXiv:2605.13292v1 Announce Type: cross Abstract: Most existing medical dialogue systems operate in a single-turn question--answering paradigm or rely on template-based datasets, limiting conversation

Interpretable Machine Learning for Antepartum Prediction of Pregnancy-Associated Thrombotic Microangiopathy Using Routine Longitudinal Laboratory Data

arXiv:2605.13786v1 Announce Type: new Abstract: Background: Pregnancy-associated thrombotic microangiopathy (P-TMA) is rare but life-threatening. Early risk prediction before overt clinical presentati

IV-ICL: Bounding Causal Effects with Instrumental Variables via In-Context Learning

arXiv:2605.12924v1 Announce Type: new Abstract: The instrumental-variables (IV) setting is standard for partial identification of causal effects when unobserved confounding makes point identification

Just Ask for a Table: A Thirty-Token User Prompt Defeats Sponsored Recommendations in Twelve LLMs

arXiv:2605.12772v1 Announce Type: new Abstract: Wu et al. (2026) showed that most frontier large language models (LLMs) recommend a sponsored, roughly twice-as-expensive flight when their system promp

researcharxiv-cs-cv

LLMs as Implicit Imputers: Uncertainty Should Scale with Missing Information

arXiv:2605.13188v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in settings where the available context is incomplete or degraded. We argue that an LLM generat

MIDST Challenge at SaTML 2025: Membership Inference over Diffusion-models-based Synthetic Tabular data

arXiv:2603.19185v2 Announce Type: replace Abstract: Synthetic data is often perceived as a silver-bullet solution to data anonymization and privacy-preserving data publishing. Drawn from generative mo

MMCL-Bench: Multimodal Context Learning from Visual Rules, Procedures, and Evidence

arXiv:2605.12703v1 Announce Type: cross Abstract: We introduce MMCL-Bench, a benchmark for multimodal context learning: learning task-local rules, procedures, and empirical patterns from visual or mix

Neural QAOA^{2}: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization

arXiv:2605.13072v1 Announce Type: cross Abstract: The quantum approximate optimization algorithm (QAOA) holds promise for combinatorial optimization but is constrained by limited qubits. While divide-

PaMM: Periodic Motif Memory for Atomistic Models with an Explicit Local-Structure Interface

arXiv:2605.13297v1 Announce Type: new Abstract: Periodic crystals repeatedly instantiate similar local coordination motifs across translated cells and chemically related structures, but current equiva

PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression

arXiv:2601.18608v3 Announce Type: replace Abstract: Shapley values have emerged as a central game-theoretic tool in explainable AI (XAI). However, computing Shapley values exactly requires 2^d game ev

Procedural Refinement by LLM-driven Algorithmic Debugging for ARC-AGI-2

arXiv:2603.20334v2 Announce Type: replace-cross Abstract: In high-complexity abstract reasoning, a system must infer a latent rule from a few examples or structured observations and apply it to unseen

Reasoning to Edit: Hypothetical Instruction-Based Image Editing with Visual Reasoning

arXiv:2507.01908v3 Announce Type: replace Abstract: Instruction-based image editing (IIE) has advanced rapidly with the success of diffusion models. However, existing efforts primarily focus on simple

scShapeBench: Discovering geometry from high dimensional scRNAseq data

arXiv:2605.12662v1 Announce Type: new Abstract: High-dimensional point cloud data arise across many scientific domains, especially single-cell biology. The shapes or topologies of these datasets deter

SynCABEL: Synthetic Contextualized Augmentation for Biomedical Entity Linking

arXiv:2601.19667v2 Announce Type: replace-cross Abstract: We present SynCABEL (Synthetic Contextualized Augmentation for Biomedical Entity Linking), a framework that addresses a central bottleneck in

Systematic Failures in Collective Reasoning under Distributed Information in Multi-Agent LLMs

arXiv:2505.11556v4 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are expected to enhance decision-making by pooling distributed information, yet syst

TokaMind for Power Grid: Cross-Domain Transfer from Fusion Plasma

arXiv:2605.11033v1 Announce Type: cross Abstract: TokaMind is a multi-modal transformer (MMT) foundation model pre-trained on tokamak plasma diagnostics data from MAST, where it was shown to outperfor

VectorSmuggle: Steganographic Exfiltration in Embedding Stores and a Cryptographic Provenance Defense

arXiv:2605.13764v1 Announce Type: cross Abstract: Modern retrieval-augmented generation (RAG) systems convert sensitive content into high-dimensional embeddings and store them in vector databases that

Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?

arXiv:2605.12684v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are now routinely deployed for visual understanding, generation, and curation. A substantial fraction of thes

A Proprioceptive-Only Benchmark for Quadruped State Estimation: ATE, RPE, and Runtime Trade-offs Between Filters and Smoothers

model-releasesarxiv-cs-ro

arXiv:2605.11674v1 Announce Type: new Abstract: We compare three state-of-the-art proprioceptive state estimators for quadruped robots: MUSE [1], the Invariant Extended Kalman Filter (IEKF) [2], and t

AgentShield: Deception-based Compromise Detection for Tool-using LLM Agents

arXiv:2605.11026v1 Announce Type: cross Abstract: Defenses against indirect prompt injection (IPI) in tool-using LLM agents share two structural weaknesses. First, they all attempt to prevent attacks

agentsarxiv-cs-cl

Beyond Localization: A Comprehensive Diagnosis of Perspective-Conditioned Spatial Reasoning in MLLMs from Omnidirectional Images

arXiv:2605.12413v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) show strong visual perception, yet remain limited in reasoning about space under changing viewpoints. We study

Beyond Manual Curation: Augmenting Targeted Protein Degradation Databases via Agentic Literature Extraction Workflows

arXiv:2605.11221v1 Announce Type: cross Abstract: Predictive models in biomedicine depend on structured assay data locked in the text, tables, and supplements of primary publications. This bottleneck

agentsarxiv-cs-lg

Beyond Text Prompts: Visual-to-Visual Generation as A Unified Paradigm

arXiv:2605.12271v1 Announce Type: new Abstract: Humans often specify and create through visual artifacts: typography sheets, sketches, reference images, and annotated scenes. Yet modern visual generat

Checkup2Action: A Multimodal Clinical Check-up Report Dataset for Patient-Oriented Action Card Generation

model-releasesarxiv-cs-cl

arXiv:2605.11533v1 Announce Type: new Abstract: Clinical check-up reports are multimodal documents that combine page layouts, tables, numerical biomarkers, abnormality flags, imaging findings, and dom

Decomposing Evolutionary Mixture-of-LoRA Architectures: The Routing Lever, the Lifecycle Penalty, and a Substrate-Conditional Boundary

model-releasesarxiv-cs-cl

arXiv:2605.11153v1 Announce Type: new Abstract: We decompose an evolutionary mixture-of-LoRA system on a from-scratch ~150M-parameter widened-D substrate (D=1536, V=32000; D/V approx 0.048; the 'widen

Decomposing the Generalization Gap in PROTAC Activity Prediction: Variance Attribution and the Inter-Laboratory Ceiling

arXiv:2605.11764v1 Announce Type: new Abstract: Machine-learning predictors of biochemical activity often exhibit large random-split-to-leave-one-target-out generalisation gaps that have been document

safetyarxiv-cs-lg

Deploying Self-Supervised Learning for Real Seismic Data Denoising

arXiv:2605.11109v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has emerged as a promising approach to seismic data denoising as it does not require clean reference data. In this work