Search: “evaluation”

CapCLIP: A Vision-Language Representation Alignment Approach for Wireless Capsule Endoscopy Analysis

arXiv:2605.08493v1 Announce Type: new Abstract: Wireless capsule endoscopy (WCE) enables non-invasive visual assessment of the small bowel, but its clinical utility is constrained by the large volume

safetyarxiv-cs-cv

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Causal Stories from Sensor Traces: Auditing Epistemic Overreach in LLM-Generated Personal Sensing Explanations

DGX agent

arXiv:2605.08590v1 Announce Type: cross Abstract: LLMs are increasingly used to explain personal sensing data, translating traces of activity and mood into natural-language accounts of why an anomalou

model-releasesarxiv-cs-ai

12 May 2026

ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts

arXiv:2603.28902v2 Announce Type: replace Abstract: Charts are central to analytical reasoning, yet existing benchmarks for chart understanding focus almost exclusively on single-chart interpretation

Clin-JEPA: A Multi-Phase Co-Training Framework for Joint-Embedding Predictive Pretraining on EHR Patient Trajectories

arXiv:2605.10840v1 Announce Type: cross Abstract: We present Clin-JEPA, a multi-phase co-training framework for joint-embedding predictive (JEPA) pretraining on EHR patient trajectories. JEPA architec

CLR-voyance: Reinforcing Open-Ended Reasoning for Inpatient Clinical Decision Support with Outcome-Aware Rubrics

arXiv:2605.09584v1 Announce Type: cross Abstract: Inpatient clinical reasoning is a sequential decision under partial observability: the clinician sees the admission so far and must choose the next ac

ColorConceptBench: A Benchmark for Probabilistic Color-Concept Understanding in Text-to-Image Models

model-releasesarxiv-cs-cl

arXiv:2601.16836v3 Announce Type: replace-cross Abstract: Text-to-image (T2I) models have advanced considerably in generating high-quality images from textual descriptions. However, their ability to a

Core-Halo Decomposition: Decentralizing Large-Scale Fixed-Point Problems

arXiv:2605.08681v1 Announce Type: cross Abstract: We study solving large-scale fixed-point equation (x^star=ar F(x^star)) with decomposition. Standard strict decomposition assigns each agent a disjoin

Counterfactual Stress Testing for Image Classification Models

arXiv:2605.10894v1 Announce Type: new Abstract: Deep learning models in medical imaging often fail when deployed in new clinical environments due to distribution shifts in demographics, scanner hardwa

applicationsarxiv-cs-cv

CrackMeBench: Binary Reverse Engineering for Agents

arXiv:2605.10597v1 Announce Type: cross Abstract: Benchmarks for coding agents increasingly measure source-level software repair, and cybersecurity benchmarks increasingly measure broad capture-the-fl

CREATE: Testing LLMs for Associative Creativity

model-releasesarxiv-cs-cl

arXiv:2603.09970v2 Announce Type: replace Abstract: A key component of creativity is associative reasoning: the ability to draw novel yet meaningful connections between concepts. We introduce CREATE,

CUDAHercules: Benchmarking Hardware-Aware Expert-level CUDA Optimization for LLMs

model-releasesarxiv-cs-lg

arXiv:2605.08467v1 Announce Type: new Abstract: Large language models show promise for automated CUDA programming, however even the strongest coding models (e.g., Claude-Opus-4.6) may still fall short

Data-Asymmetric Latent Imagination and Reranking for 3D Robotic Imitation Learning

arXiv:2605.10166v1 Announce Type: new Abstract: Robotic imitation learning typically assumes access to optimal demonstrations, yet real-world data collection often yields suboptimal, exploratory, or e

applicationsarxiv-cs-ro

DataMaster: Towards Autonomous Data Engineering for Machine Learning

arXiv:2605.10906v1 Announce Type: cross Abstract: As model families, training recipes, and compute budgets become increasingly standardized, further gains in machine learning systems depend increasing

agentsarxiv-cs-ai

Detecting Multi-Agent Collusion Through Multi-Agent Interpretability

arXiv:2604.01151v2 Announce Type: replace Abstract: As LLM agents are increasingly deployed in multi-agent systems, they introduce risks of covert coordination that may evade standard forms of human o

DexWrist: A Robotic Wrist for Constrained and Dynamic Manipulation

arXiv:2507.01008v3 Announce Type: replace Abstract: Development of dexterous manipulation hardware has primarily focused on hands and grippers. However, these end-effectors are often paired with bulky

safetyarxiv-cs-ro

Discriminative Span as a Predictor of Synthetic Data Utility via Classifier Reconstruction

arXiv:2605.09697v1 Announce Type: new Abstract: In many real-world computer vision applications, including medical imaging and industrial inspection, binary classification tasks are characterized by a

applicationsarxiv-cs-cv

Do Linear Probes Generalize Better in Persona Coordinates?

arXiv:2605.09391v1 Announce Type: new Abstract: It is becoming increasingly necessary to have monitors check for harmful behaviors during language model interactions, but text-only monitoring has not

Drum Synthesis from Expressive Drum Grids via Neural Audio Codecs

arXiv:2605.10281v1 Announce Type: cross Abstract: Generating realistic drum audio directly from symbolic representations is a challenging task at the intersection of music perception and machine learn

DynaMiCS: Fine-tuning LLMs with Performance Constraints using Dynamic Mixtures

arXiv:2605.10770v1 Announce Type: new Abstract: Multi-domain fine-tuning of large language models requires improving performance on target domains while preserving performance on constrained domains,

safetyarxiv-cs-lg

E-TCAV: Formalizing Penultimate Proxies for Efficient Concept Based Interpretability

arXiv:2605.10261v1 Announce Type: new Abstract: TCAV (Testing with Concept Activation Vectors) is an interpretability method that assesses the alignment between the internal representations of a train

EchoFake: A Replay-Aware Dataset for Practical Speech Deepfake Detection

arXiv:2510.19414v2 Announce Type: replace-cross Abstract: The growing prevalence of speech deepfakes has raised serious concerns, particularly in real-world scenarios such as telephone fraud and ident

applicationsarxiv-cs-ai

EduStory: A Unified Framework for Pedagogically-Consistent Multi-Shot STEM Instructional Video Generation

arXiv:2605.09378v1 Announce Type: cross Abstract: Long-horizon video generation has advanced in visual quality, yet existing methods still struggle to maintain knowledge consistency and coherent pedag

EvoDriveVLA: Evolving Driving VLA Models via Collaborative Perception-Planning Distillation

arXiv:2603.09465v3 Announce Type: replace-cross Abstract: Vision-Language-Action models have shown great promise for autonomous driving, yet they suffer from degraded perception after unfreezing the v

agentsarxiv-cs-ai

Evolving-RL: End-to-End Optimization of Experience-Driven Self-Evolving Capability within Agents

arXiv:2605.10663v1 Announce Type: new Abstract: Experience-driven self-evolving agents aim to overcome the static nature of large language models by distilling reusable experience from past interactio

researcharxiv-cs-ai

EvoMAS: Learning Execution-Time Workflows for Multi-Agent Systems

arXiv:2605.08769v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems have shown strong potential on complex tasks through agent specialization, tool use, and collaborat

EvoStreaming: Your Offline Video Model Is a Natively Streaming Assistant

arXiv:2605.10343v1 Announce Type: cross Abstract: Streaming video understanding demands more than watching longer videos: assistants must decide when to speak in real time, balancing responsiveness ag

Explainable Machine Learning Framework for Cardiovascular Disease Diagnosis and Prognosis

arXiv:2507.11185v2 Announce Type: replace-cross Abstract: Heart disease continues to pose a critical worldwide health issue, more specifically in areas with insufficient access to healthcare infrastru

applicationsarxiv-cs-ai

Explicit Reasoning Makes Better Judges: A Systematic Study on Accuracy, Efficiency, and Robustness

arXiv:2509.13332v2 Announce Type: replace Abstract: As Large Language Models (LLMs) are increasingly adopted as automated judges in benchmarking and reward modeling, ensuring their reliability, effici

Exploring and Exploiting Stability in Latent Flow Matching

arXiv:2605.08398v1 Announce Type: cross Abstract: In this work, we show that Latent Flow-Matching (LFM) models are robust to different types of perturbations, including data reduction and model capaci

researcharxiv-cs-cv

Exploring the AI Obedience: Why is Generating a Pure Color Image Harder than CyberPunk?

arXiv:2603.00166v2 Announce Type: replace-cross Abstract: Recent advances in generative AI have shown human-level performance in complex content creation. However, we identify a 'Paradox of Simplicity

FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

arXiv:2605.08820v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-generated images have become increasingly realistic and readily adaptable to concrete real-world claims, creating new cha

Free Energy Manifold: Score-Based Inference for Hybrid Bayesian Networks

arXiv:2605.09839v1 Announce Type: cross Abstract: We introduce the Free Energy Manifold (FEM), a score-trained conditional energy model specialized for inference in hybrid Bayesian networks with discr

researcharxiv-cs-ai

Generative Actor-Critic with Soft Bridge Policies

model-releasesarxiv-cs-lg

arXiv:2605.08733v1 Announce Type: new Abstract: Expressive generative policies such as diffusion and flow models are appealing for MaxEnt online reinforcement learning because of their ability to mode

Generative Adversarial Post-Training Mitigates Reward Hacking in Live Human-AI Music Interaction

arXiv:2511.17879v4 Announce Type: replace Abstract: Most applications of generative AI involve a sequential interaction in which a person inputs a prompt and waits for a response, and where reaction t

safetyarxiv-cs-lg

GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping

model-releasesarxiv-cs-lg

arXiv:2603.12275v1 Announce Type: cross Abstract: Unlearning knowledge is a pressing and challenging task in Large Language Models (LLMs) because of their unprecedented capability to memorize and dige

HAMLET: A Hierarchical and Adaptive Multi-Agent Framework for Live Embodied Theatrics

arXiv:2507.15518v5 Announce Type: replace Abstract: Creating an immersive and interactive theatrical experience is a long-term goal in the field of interactive narrative. The emergence of large langua

agentsarxiv-cs-ai

IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs

arXiv:2605.10267v1 Announce Type: new Abstract: In industrial procurement, an LLM answer is useful only if it survives a standards check: recommended material must match operating condition, every par

Kinetic-Optimal Scheduling with Moment Correction for Metric-Induced Discrete Flow Matching in Zero-Shot Text-to-Speech

arXiv:2605.09386v1 Announce Type: cross Abstract: Metric-induced discrete flow matching (MI-DFM) exploits token-latent geometry for discrete generation, but its practical use is limited by two issues:

researcharxiv-cs-ai

Language Models Without a Trainable Input Embedding Table: Learning from Fixed Minimal Binary Token Codes

model-releasesarxiv-cs-cl

arXiv:2605.09751v1 Announce Type: new Abstract: Trainable input embedding tables are a standard component of modern language models. We ask whether they are actually necessary at the input interface.

Tutorials

Learning from Acceptance: Cumulative Regret in the Game of Coding

arXiv:2605.09754v1 Announce Type: cross Abstract: Classical coding-theoretic guarantees often rely on trust assumptions, such as requiring sufficiently many honest nodes compared with adversarial ones

tutorialsarxiv-cs-lg

Learning Multi-Indicator Weights for Data Selection: A Joint Task-Model Adaptation Framework with Efficient Proxies

arXiv:2605.09665v1 Announce Type: cross Abstract: Data selection is a key component of efficient instruction tuning for large language models, as recent work has shown that data quality often matters

Learning When to Jump for Off-road Navigation

arXiv:2602.00877v2 Announce Type: replace Abstract: Low speed does not always guarantee safety in off-road driving. For instance, crossing a ditch may be risky at a low speed due to the risk of gettin

safetyarxiv-cs-ro

LimeCross: Context-Conditioned Layered Image Editing with Structural Consistency

model-releasesarxiv-cs-cv

arXiv:2605.10319v1 Announce Type: new Abstract: Layered image assets are widely used in real-world creative workflows, enabling non-destructive iteration and flexible re-composition. Recent advances i

Local Ai

LLM-Guided Monte Carlo Tree Search over Knowledge Graphs: Composing Mechanistic Explanations for Drug-Disease Pairs

arXiv:2605.09542v1 Announce Type: new Abstract: Extracting multi-step explanations from knowledge graphs poses a combinatorial challenge requiring both heuristic guidance (as candidates proliferate wi

local-aiarxiv-cs-ai

Low-Cost Neural Radiance Fields

arXiv:2605.09312v1 Announce Type: new Abstract: Neural Radiance Fields (NeRF) achieve high-quality novel-view synthesis, but their long training times and reliance on dense input views limit accessibi

researcharxiv-cs-cv

Low-Cost Stereo Vision for Robust 3D Positioning of Thin Radiata Pine Branches in Autonomous Drone Pruning

arXiv:2605.08213v1 Announce Type: new Abstract: Manual pruning of radiata pine, a species of major economic importance to New Zealand forestry, is hazardous, labour-intensive, and increasingly constra

agentsarxiv-cs-cv

Local Ai

Mazocarta: A Seeded Procedural Deckbuilder for Instrumented Game Development

arXiv:2605.08319v1 Announce Type: cross Abstract: Mazocarta is a seeded procedural tactical deckbuilder implemented in Rust, compiled to WebAssembly for browser play, and executable natively for simul

local-aiarxiv-cs-ai

MC^2: Monte Carlo Correction for Fast Elliptic PDE Solving

arXiv:2605.09288v1 Announce Type: cross Abstract: Partial differential equation (PDE) solvers underpin scientific computing, but real-world deployment is bounded by compute. Classical Monte Carlo solv