Search: “evaluation”

Optimizing Visual Generative Models via Distribution-wise Rewards

arXiv:2607.02291v1 Announce Type: new Abstract: Conventional reinforcement learning strategies for visual generation typically employ sample-wise reward functions, yet this practice frequently results

safetyarxiv-cs-lg

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Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander

DGX agent

arXiv:2607.01736v1 Announce Type: cross Abstract: We study how to predict the downstream closed-loop performance of a learned latent world model from validation-time diagnostics alone. Choosing the ri

safetyarxiv-cs-ai

3 Jul 2026

StatEval: A Comprehensive Benchmark for Large Language Models in Statistics

arXiv:2510.09517v2 Announce Type: replace Abstract: Despite rapid advances in large language models (LLMs), statistical reasoning remains underrepresented in existing LLM benchmarks, which often do no

TestEvo-Bench: An Executable and Live Benchmark for Test and Code Co-Evolution

arXiv:2607.02469v1 Announce Type: cross Abstract: Software tests and code evolve together: a code change should be followed by new or updated tests that record the new software behavior. Yet existing

The Moving Eye: Enhancing VLA Spatial Generalization via Hybrid Dynamic Data Collection

arXiv:2607.02322v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown remarkable promise in generalized robotic manipulation. However, their spatial generalization remains fra

researcharxiv-cs-ro

Towards Learning Representations of Policies in Two-Player Zero-Sum Imperfect-Information Games

arXiv:2607.01498v1 Announce Type: new Abstract: We investigate the problem of learning useful policy representations (embeddings) in two-player zero-sum imperfect-information games. We make three cont

safetyarxiv-cs-lg

Verifiable Knowledge Expansion through Retrieval-Grounded Formal Concept Analysis

arXiv:2607.01773v1 Announce Type: new Abstract: Ontology construction requires deciding which objects, attributes, and structural relations should be accepted as valid knowledge. Language models can p

VLAFlow: A Unified Training Framework for Vision-Language-Action Models via Co-training and Future Latent Alignment

arXiv:2607.01586v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) have recently advanced robotic manipulation, yet the effects of different robot-data pre-training paradigms remai

We are pleased to present our latest research at #ICML2026, “Bridging Spherical Black-Box Optimizers” https://arxiv.org/abs/2606.25761 When …

We are pleased to present our latest research at #ICML2026, “Bridging Spherical Black-Box Optimizers” https://arxiv.org/abs/2606.25761 When optimizing through simulators, external APIs, or in reinforc

researchdavid-ha--x

What LLM Agents Say When No One Is Watching: Social Structure and Latent Objective Emergence in Multi-Agent Debates

arXiv:2607.02507v1 Announce Type: new Abstract: LLM agents will increasingly act in socially structured settings where role, audience, and relational context can shape what is advantageous or costly t

Adaptive Perturbation Selection for Contrastive Audio Decoding

arXiv:2607.00247v1 Announce Type: cross Abstract: Large audio-language models (LALMs) frequently hallucinate by overriding acoustic evidence with language priors. While contrastive decoding (CD) offer

An LLM-Based Framework for Intent-Driven Network Topology Design

arXiv:2607.00292v1 Announce Type: cross Abstract: Designing deployable and resilient network topologies from natural language requirements remains a challenging problem in network automation. This wor

AutoSpeed: Annotation-Free Stage-Adaptive Motion Speed Learning for Robot Manipulation

arXiv:2607.01051v1 Announce Type: new Abstract: Different stages of manipulation tasks exhibit varying levels of difficulty, suggesting stage-dependent motion speeds and temporal prediction horizons.

Comparing Large Language Models on Scrum Certification-Style Questions: Accuracy, Stability, and Error Patterns

arXiv:2607.00048v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in exam- and certification-style question answering tasks, where their ability to retrieve, interpr

Constrained Bayesian Optimisation with Multiple Information Sources

arXiv:2607.00865v1 Announce Type: new Abstract: Bayesian Optimisation (BO) under unknown constraints is particularly challenging when feasible regions are small. In such settings, existing methods tha

applicationsarxiv-cs-lg

CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization

arXiv:2511.05747v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) reasoning enhances the problem-solving ability of large language models (LLMs) but leads to substantial inference overhead, l

Distributed Multi Robot Lunar Cargo Transportation via Phase Decomposed Reinforcement Learning

arXiv:2607.00160v1 Announce Type: new Abstract: Modular reconfigurable robotic systems provide a scalable solution for cooperative surface operations in future lunar missions. However, cooperative car

EchoRisk: A Multicentre Echocardiography Dataset and Benchmark for Cardio-Oncology

arXiv:2607.01039v1 Announce Type: cross Abstract: Therapy-induced cardiotoxicity is the leading non-oncological cause of treatment interruption in breast cancer patients, yet early, automated risk str

EmbodimentSemantic: A Spatial Scene-Graph Dataset and Benchmark for Vision-Language Models on Embodied Manipulation Trajectories

model-releasesarxiv-cs-ro

arXiv:2607.00020v1 Announce Type: new Abstract: Spatial grounding remains a key limitation of vision-language-action (VLA) systems for robotic manipulation. While current models can recognize objects

Agents

From Personas to Plot: Character-Grounded Multi-Agent Story Generation for Long-Form Narratives

arXiv:2607.00918v1 Announce Type: cross Abstract: Although large language models (LLMs) have demonstrated impressive creative fiction generation, they struggle to maintain narrative consistency and co

agentsarxiv-cs-ai

Local Ai

Korzhinskii-Net: Physics-Informed Neural Network for Sub-Surface Mineral Prospectivity Modelling

arXiv:2606.13695v2 Announce Type: replace-cross Abstract: Mineral prospectivity modelling (MPM) underpins exploration economics, yet most operational pipelines reduce to data-driven classifiers traine

local-aiarxiv-cs-ai

Learning Category-level Last-meter Navigation from RGB Demonstrations of a Single-instance

arXiv:2512.11173v4 Announce Type: replace Abstract: Achieving precise positioning of the mobile manipulator's base is essential for successful manipulation actions that follow. Most of the RGB-based n

MemSyco-Bench: Benchmarking Sycophancy in Agent Memory

arXiv:2607.01071v1 Announce Type: cross Abstract: Memory has emerged as a cornerstone of modern LLM-based agents, supporting their evolution from single-turn assistants to long-term collaborators. How

MolSafeEval: A Benchmark for Uncovering Safety Risks in AI-Generated Molecules

arXiv:2607.00464v1 Announce Type: cross Abstract: Current molecular generation benchmarks emphasize task complexity, molecule novelty, and property alignment; they largely overlook a critical concern:

OmniFall: From Staged Through Synthetic to Wild, A Unified Multi-Domain Dataset for Robust Fall Detection

model-releasesarxiv-cs-cv

arXiv:2505.19889v3 Announce Type: replace Abstract: Visual fall detection models are usually trained on small, staged datasets. Their real-world utility remains unclear; such data lacks diversity and

PedNStream: Scalable Network Flow Simulation for Pedestrian Traffic Management

arXiv:2607.01021v1 Announce Type: new Abstract: Large-scale crowd management requires pedestrian simulations that are both computationally efficient and compatible with feedback-based control. However

applicationsarxiv-cs-ai

PHREEQC-MCQ-200: A Diagnostic Benchmark for Tool-Augmented Scientific Simulator Agents

arXiv:2607.00436v1 Announce Type: new Abstract: Large language model agents are increasingly connected to scientific software, yet it remains unclear when tool access makes scientific computation more

Reading Order Inference for Complex Document Layouts

arXiv:2607.01018v1 Announce Type: cross Abstract: Reading order inference remains a critical bottleneck in the digitization of complex historical manuscripts, where pages contain multiple spatially in

Robots Ask the Way: Communication-Enabled Social Navigation

arXiv:2607.01044v1 Announce Type: new Abstract: Assistive autonomous robots operating in multi-agent environments require efficient strategies to locate specific individuals among multiple residents.

Seahorse: A Unified Benchmarking Framework for Spatiotemporal Event Modeling

model-releasesarxiv-cs-lg

arXiv:2607.01022v1 Announce Type: new Abstract: Spatiotemporal point processes (STPPs) model event data in continuous time and space, with applications in mobility, epidemiology, and public safety. Re

Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity

arXiv:2607.00248v1 Announce Type: new Abstract: We present Seed2.0, a model series that takes a meaningful step toward solving complex, real-world tasks. Our approach begins with identifying users' ge

applicationsarxiv-cs-ai

Spectroscopy Analysis with Machine Learning Regression for the Quantification of Carbon and Nitrogen Contents in Inceptisol and Oxisol Soil Types: Comparing Different Preprocessing and Validation methods as well as Feature Importance

arXiv:2607.00834v1 Announce Type: new Abstract: Near-Infrared (NIR) spectroscopy has emerged as a promising alternative to traditional soil analysis methods, offering advantages such as speed, low cos

researcharxiv-cs-lg

StochasT: Learning with Stochastic Turn Depth for Visual Instruction Tuning

arXiv:2607.00465v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) rely extensively on Visual Instruction Tuning (VIT) to elicit their multimodal reasoning capabilities. However, w

The Illusion of High Utility in Safety Alignment of Text-to-Image Diffusion Models

arXiv:2607.00402v1 Announce Type: cross Abstract: Safety alignment of text-to-image (T2I) diffusion models aims to suppress harmful generations while preserving utility on benign prompts. Recent metho

Towards an automated AI-based framework for floor plan compliance checks for residential buildings

arXiv:2607.00015v1 Announce Type: cross Abstract: To improve residents' well-being in Australia's urban areas, governments have introduced policy reforms such as SEPP65, BADS, and SPP7.3 to enhance ap

Towards Developing a Multimodal Chat Assistant for University Stakeholders: RAG-based Approach

arXiv:2607.01115v1 Announce Type: cross Abstract: University stakeholders often face difficulties in accessing timely and reliable information, especially in developing countries, where there are very

Towards Metric-Agnostic Trajectory Forecasting

model-releasesarxiv-cs-cv

arXiv:2607.01133v1 Announce Type: new Abstract: Accurate trajectory forecasting of surrounding traffic participants is a core capability for autonomous driving, enabling vehicles to anticipate behavio

A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems

arXiv:2606.31639v1 Announce Type: cross Abstract: Large language models are no longer only text generators. They are increasingly embedded in retrieval pipelines, enterprise assistants, coding environ

A Self-Evolving Agentic System for Automated Generation and Execution of Biological Protocols

arXiv:2606.31763v1 Announce Type: new Abstract: Autonomous wet-lab experimentation requires more than plausible protocol text: biological intent, quantitative procedures, device constraints and experi

A Semantic-Layer-Mediated Agent for Natural Language to SQL over Heterogeneous Enterprise Databases

arXiv:2606.31041v1 Announce Type: new Abstract: Natural language-to-SQL (NL2SQL) over real-world enterprise databases remains significantly more challenging than on academic benchmarks. Enterprise sch

Accelerometry-Derived Digital Biomarkers for Cardiometabolic Risk: A Population-Representative Tabular Benchmark with Uncertainty Quantification

arXiv:2606.30702v1 Announce Type: cross Abstract: Structured tabular data dominates clinical medicine, yet existing benchmarks fail to reflect real-world properties like complex survey sampling, demog

AgentBound: Verifiable Behavioral Governance for Autonomous AI Agents

arXiv:2606.30970v1 Announce Type: new Abstract: Autonomous AI agents increasingly perform consequential actions on behalf of human principals, including financial transactions, external communications

AI-Generated PowerShell Malware: An Experimental Framework and Dataset

arXiv:2606.30819v1 Announce Type: cross Abstract: Generative AI has emerged as a significant cybersecurity threat, with several recent attack campaigns leveraging LLMs to generate code for malicious p

applicationsarxiv-cs-ai

AION: Aerial Indoor Object-Goal Navigation Using Dual-Policy Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2601.15614v3 Announce Type: replace Abstract: Object-Goal Navigation (ObjectNav) requires an agent to autonomously explore an unknown environment and navigate toward target objects specified by

AlloyDB AI Functions - now with revolutionary performance boosts and cost savings

model-releasesgoogle-cloud-ai

AlloyDB is an AI-native database—it isn’t just a passive data store, it intelligently understands and processes your data. With AlloyDB, you get industry-leading vector and hybrid search, near 100% ac

AMALIA-VL: A Native European Portuguese Open-Source Vision and Language Model

arXiv:2606.19100v2 Announce Type: replace Abstract: Large Vision and Language Models (LVLMs) have advanced rapidly, yet European Portuguese (pt-PT) remains systematically underserved by existing open-

safetyarxiv-cs-cv

An Empirical Study of Security Calibration in Large Language Models for Code

model-releasesarxiv-cs-lg

arXiv:2606.31159v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly transforming software development, yet their use in security-critical contexts raises a key question: do mode

AutoTrainess: Teaching Language Models to Improve Language Models Autonomously

arXiv:2606.31551v1 Announce Type: new Abstract: Training language models (LMs) remains a highly human-intensive process, even as frontier language model agents become increasingly capable at software