Search: “evaluation”

NavRL++: A System-Level Framework for Improving Sim-to-Real Transfer in Reinforcement Learning-Based Robot Navigation

arXiv:2605.15559v1 Announce Type: new Abstract: Recent years have witnessed significant progress in autonomous navigation using reinforcement learning. However, existing approaches largely emphasize r

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Local Ai

Neural Policy Composition from Free Energy Minimization

DGX agent

arXiv:2512.04745v3 Announce Type: replace-cross Abstract: The ability to flexibly compose previously acquired skills to execute intelligent behaviors is a hallmark of natural intelligence. Such compos

local-aiarxiv-cs-ai

18 May 2026

Neurosymbolic Object-Centric Learning with Distant Supervision

arXiv:2506.16129v2 Announce Type: replace Abstract: Neurosymbolic learning can use symbolic rules to provide supervision for latent concepts from weak labels, but it commonly assumes that the entities

researcharxiv-cs-cv

Njord: A Probabilistic Graph Neural Network for Ensemble Ocean Forecasting

arXiv:2605.15470v1 Announce Type: new Abstract: Ocean dynamics are inherently chaotic, yet existing machine learning ocean models produce only deterministic forecasts. We introduce Njord, a probabilis

Offline Semantic Guidance for Efficient Vision-Language-Action Policy Distillation

arXiv:2605.16241v1 Announce Type: cross Abstract: Billion-parameter Vision-Language-Action (VLA) policies have recently shown impressive performance in robotic manipulation, yet their size and inferen

OHP-RL: Online Human Preference as Guidance in Reinforcement Learning for Robot Manipulation

arXiv:2605.15971v1 Announce Type: new Abstract: While reinforcement learning (RL) enables robots to acquire skills autonomously, its real-world deployment is severely limited by inefficient and unsafe

On the Stability of Growth in Structural Plasticity

arXiv:2605.15435v1 Announce Type: new Abstract: Standard deep-learning pipelines usually choose the network architecture before training and keep it fixed throughout optimization. In contrast, a model

researcharxiv-cs-lg

Ontology for Policing: Conceptual Knowledge Learning for Semantic Understanding and Reasoning in Law Enforcement Reports

arXiv:2605.15978v1 Announce Type: cross Abstract: Law enforcement reports contain structured fields and written narratives. However, many incident facts that are needed for review, police training, an

OpenFrontier: General Navigation with Visual-Language Grounded Frontiers

arXiv:2603.05377v2 Announce Type: replace-cross Abstract: Open-world navigation requires robots to make decisions in complex everyday environments while adapting to flexible task requirements. Convent

Agents

Optimized Three-Dimensional Photovoltaic Structures with LLM guided Tree Search

arXiv:2605.16191v1 Announce Type: new Abstract: We present a case study for how AI coding systems can be used to generate novel scientific hypotheses. We combine a generic coding agent (Google's AntiG

agentsarxiv-cs-cl

PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control

arXiv:2605.15963v1 Announce Type: new Abstract: Large vision-language models have significantly advanced GUI agents, enabling executable interaction across web, mobile, and desktop interfaces. Yet the

Painless Activation Steering: An Automated, Lightweight Approach for Post-Training Large Language Models

arXiv:2509.22739v3 Announce Type: replace-cross Abstract: Language models (LMs) are typically post-trained for desired capabilities and behaviors via weight-based or prompt-based steering, but the for

PanoWorld: Geometry-Consistent Panoramic Video World Modeling

arXiv:2605.15391v1 Announce Type: cross Abstract: We present PanoWorld, a panoramic video world model that generates geometry-consistent 360egree video from a single image and a caption. Existing pano

PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment

arXiv:2605.15654v1 Announce Type: new Abstract: Real-world autonomous driving, particularly in urban environments with numerous corner cases, requires rigorous testing to ensure product safety and rob

Pessimistic Risk-Aware Policy Learning in Contextual Bandits

arXiv:2605.15620v1 Announce Type: cross Abstract: We study risk-aware offline policy learning, aiming to learn a decision rule from logged data that is optimal under general risk criteria. This proble

safetyarxiv-cs-lg

PhyDetEx: Detecting and Explaining the Physical Plausibility of T2V Models

model-releasesarxiv-cs-cv

arXiv:2512.01843v2 Announce Type: replace Abstract: Driven by the growing capacity and training scale, Text-to-Video (T2V) generation models have recently achieved substantial progress in video qualit

Polynomial Neural Sheaf Diffusion: A Spectral Filtering Approach on Cellular Sheaves

arXiv:2512.00242v3 Announce Type: replace-cross Abstract: Sheaf Neural Networks equip graph structures with a cellular sheaf: a geometric structure which assigns local vector spaces (stalks) and a lin

PRB-RUPFormer: A Recursive Unified Probabilistic Transformer for Residual PRB Forecasting

arXiv:2605.15363v1 Announce Type: new Abstract: Accurate forecasting of residual Physical Resource Blocks (PRBs) is critical for proactive network slice provisioning, energy-efficient operation, and s

researcharxiv-cs-lg

Applications

Preprocessing Algorithm Leveraging Geometric Modeling for Scale Correction in Hyperspectral Images for Improved Unmixing Performance

arXiv:2508.08431v3 Announce Type: replace-cross Abstract: Spectral variability significantly impacts the accuracy and convergence of hyperspectral unmixing algorithms. Many methods address complex spe

applicationsarxiv-cs-cv

Pretraining Objective Matters in Extreme Low-Data FGVC: A Backbone-Controlled Study

arXiv:2605.15599v1 Announce Type: cross Abstract: Extreme low-data fine-grained classification is common in expert domains where labeling is expensive, yet practitioners still need principled guidance

Applications

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing

arXiv:2509.20349v3 Announce Type: replace Abstract: Accurate time-series forecasting for complex physical systems is the backbone of modern industrial monitoring and control, yet deep learning models

applicationsarxiv-cs-lg

Propagating Unsafe Actions in LLM Controlled Multi-Robot Collaboration via Single Robot Compromise

arXiv:2605.15641v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as general planners in embodied intelligence, enabling high level coordination and low level task pla

Quantum Feature Pyramid Gating for Seismic Image Segmentation

arXiv:2605.15370v1 Announce Type: cross Abstract: Accurate salt-body delineation is essential for seismic interpretation because salt structures distort wave propagation, complicate velocity-model bui

ReactiveGWM: Steering NPC in Reactive Game World Models

arXiv:2605.15256v1 Announce Type: new Abstract: Current game world models simulate environments from a subjective, player-centric perspective. However, by treating the Non-Player Character (NPC) merel

Reading the Cell, Designing the Cure: Perturbation-Conditioned Molecular Diffusion for Function-Oriented Drug Design

arXiv:2605.15243v1 Announce Type: cross Abstract: When reliable target structures are unavailable at scale or phenotypes arise from dysregulated pathways, transcriptomic perturbations provide a system

Reducing the Safety Tax in LLM Safety Alignment with On-Policy Self-Distillation

arXiv:2605.15239v1 Announce Type: new Abstract: Safety alignment often improves robustness to harmful queries at the cost of reasoning ability, a tradeoff known as the safety tax. A common cause is di

Reference-Free Reinforcement Learning Fine-Tuning for MT: A Seq2Seq Perspective

arXiv:2605.15976v1 Announce Type: cross Abstract: Production machine translation relies overwhelmingly on encoder-decoder Seq2Seq models, yet reinforcement learning approaches to MT fine-tuning have l

Reference Games as a Testbed for the Alignment of Model Uncertainty and Clarification Requests

arXiv:2601.07820v2 Announce Type: replace Abstract: In human conversation, both interlocutors play an active role in maintaining mutual understanding. When listeners are uncertain about what speakers

safetyarxiv-cs-cl

Representation Without Reward: A JEPA Audit for LLM Fine-Tuning

arXiv:2605.15394v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) propose that a model should learn more useful abstractions when trained to predict latent representat

Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models

arXiv:2605.15792v1 Announce Type: new Abstract: The long-standing goal of multimodal AI is to build unified models in which visual understanding and visual generation mutually enhance one another. Des

Runtime-Orchestrated Second-Order Optimization for Scalable LLM Training

arXiv:2605.16184v1 Announce Type: cross Abstract: Second-order methods offer an attractive path toward more sample-efficient LLM training, but their practical use is often blocked by the systems cost

SAFE Quantum Machine Learning with Variational Quantum Classifiers

arXiv:2605.16067v1 Announce Type: new Abstract: We propose a variational quantum classifier operating on high dimensional deep representations via amplitude encoding, stabilized by a learnable classic

safetyarxiv-cs-lg

ScreenSearch: Uncertainty-Aware OS Exploration

arXiv:2605.16024v1 Announce Type: new Abstract: Desktop GUI agents operate under partial observability: visually similar screens can correspond to different underlying workflow states, so locally plau

Searching on a Budget: HW-NAS with 10 Latency Probes

arXiv:2504.00663v2 Announce Type: replace Abstract: Existing hardware-aware NAS (HW-NAS) methods typically assume access to precise information circa the target device, either via analytical approxima

Seeing What Matters: Visual Preference Policy Optimization for Visual Generation

arXiv:2511.18719v4 Announce Type: replace Abstract: Reinforcement learning (RL) has become a powerful tool for post-training visual generative models, with Group Relative Policy Optimization (GRPO) in

Local Ai

Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning

arXiv:2605.15997v1 Announce Type: new Abstract: Recent progress in deep learning has significantly advanced CT image analysis, particularly for segmentation tasks. However, these advances are largely

local-aiarxiv-cs-cv

Self-Supervised Learning by Curvature Alignment

arXiv:2511.17426v2 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) has recently advanced through non-contrastive methods that couple an invariance term with variance, covariance,

SemanticOpt: Towards LLM-Based Semantic Black-Box Optimization

arXiv:2510.25404v3 Announce Type: replace-cross Abstract: Optimizing an experimental system can be extremely challenging when each experiment is expensive, time-consuming, or difficult to perform. Exi

SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization

arXiv:2604.02268v2 Announce Type: replace Abstract: Agent skills, structured packages of procedural knowledge and executable resources that agents dynamically load at inference time, have become a rel

safetyarxiv-cs-lg

SkillSmith: Compiling Agent Skills into Boundary-Guided Runtime Interfaces

arXiv:2605.15215v1 Announce Type: new Abstract: Recently, skills have been widely adopted in large language model (LLM)-based agent systems across various domains. In existing frameworks, skills are t

SLIP & ETHICS: Graduated Intervention for AI Emotional Companions

arXiv:2605.15915v1 Announce Type: cross Abstract: AI emotional companions face a safety-rapport paradox: restrictive safeguards can damage supportive alliance, while permissive systems risk user harm.

Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models

arXiv:2602.01970v2 Announce Type: replace Abstract: Reinforcement learning enhances the reasoning capabilities of large language models but often involves high computational costs due to rollout-inten

SOLAR: Self-supervised Joint Learning for Symmetric Multimodal Retrieval

model-releasesarxiv-cs-cv

arXiv:2605.15868v1 Announce Type: new Abstract: In this work, we address the critical yet underexplored challenge of symmetric multimodal-to-multimodal (MM2MM) retrieval, where queries and contexts ar

Agents

Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution

arXiv:2605.15301v1 Announce Type: new Abstract: Large language models (LLMs) still struggle with the rigorous reasoning demands of hard competitive programming. While recent multi-agent frameworks att

agentsarxiv-cs-ai

Local Ai

Sound Sparks Motion: Audio and Text Tuning for Video Editing

arXiv:2605.15307v1 Announce Type: cross Abstract: Motion-centric video editing remains difficult for large generative video models, which often respond well to appearance changes but struggle to produ

local-aiarxiv-cs-cv

STS: Efficient Sparse Attention with Speculative Token Sparsity

model-releasesarxiv-cs-cl

arXiv:2605.15508v1 Announce Type: cross Abstract: The quadratic complexity of attention imposes severe memory and computational bottlenecks on Large Language Model (LLM) inference. This challenge is p

SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference

arXiv:2605.15488v1 Announce Type: new Abstract: Survival analysis provides a powerful statistical framework for modeling time-to-event outcomes in the presence of censoring. However, selecting an appr

Syntax Without Semantics: Teaching Large Language Models to Code in an Unseen Language

arXiv:2605.15607v1 Announce Type: new Abstract: Large language models (LLMs) achieve high pass rates on code generation benchmarks, yet whether they can transfer this ability to languages absent from

researcharxiv-cs-cl