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Neuron-Aware Data Selection for Annotation-Free LLM Self-Distillation

arXiv:2607.02460v1 Announce Type: cross Abstract: Post-training large language models (LLMs) without real-world interaction feedback or human-labeled supervision remains challenging, particularly in s

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NEUROSYMLAND: Neuro-Symbolic Landing-Site Assessment for Robust and Edge-Deployable UAV Autonomy

DGX agent

arXiv:2607.02277v1 Announce Type: new Abstract: Safe landing-site assessment in unstructured environments remains a key challenge for autonomous UAV deployment, as vision-only learning approaches ofte

model-releasesarxiv-cs-ro

3 Jul 2026

Tutorials

Non-synchronism in Global Usage of Research Methods in Library and Information Science from 1990 to 2019

arXiv:2607.01833v1 Announce Type: cross Abstract: The global development of Library and Information Science (LIS) is influenced by various factors such as the economy, society, culture, discipline, tr

tutorialsarxiv-cs-cl

Object Aligner: A Configurable JSON Schema Similarity Score for Graphs, Applied to LLM Prompt Optimization

arXiv:2607.01972v1 Announce Type: cross Abstract: Large language models (LLMs) are often asked to produce JSON conforming to a fixed schema, powering information extraction, tool calling, agentic plan

Object-centric LeJEPA

arXiv:2607.02404v1 Announce Type: cross Abstract: Image encoders trained with LeJEPA can deliver strong features for downstream tasks, but, like other image-level self-supervised methods, typically re

researcharxiv-cs-lg

Office Comprehension Benchmark

arXiv:2607.01245v1 Announce Type: cross Abstract: We introduce Office Comprehension Bench (OCB), the first public benchmark to jointly evaluate LLM systems on Word, Excel, and PowerPoint comprehension

OmniGAIA: Towards Native Omni-Modal AI Agents

arXiv:2602.22897v3 Announce Type: replace Abstract: Human intelligence naturally intertwines omni-modal perception -- spanning vision, audio, and language -- with complex reasoning and tool usage to i

Tutorials

On the Asymptotics of Self-Supervised Pre-training: Two-Stage M-Estimation and Representation Symmetry

arXiv:2603.27631v2 Announce Type: replace Abstract: Self-supervised pre-training, where large corpora of unlabeled data are used to learn representations for downstream fine-tuning, has become a corne

tutorialsarxiv-cs-lg

On the Dimension-Free Approximation of Deep Neural Networks for Symmetric Korobov Functions

arXiv:2511.12398v2 Announce Type: replace Abstract: Deep neural networks have been widely used as universal approximators for functions with inherent physical structures, including permutation symmetr

researcharxiv-cs-lg

On the Limits of Steering Vectors for Preference-Aligned Generation

arXiv:2607.01802v1 Announce Type: new Abstract: Steering vectors have emerged as a promising approach to controlled text generation, offering interpretable, training-free mechanisms for shaping model

On the Role of Computation in Reinforcement Learning

arXiv:2602.05999v4 Announce Type: replace Abstract: How does the amount of compute available to a reinforcement learning (RL) policy affect its learning? Can policies using a fixed amount of parameter

On the Role of Directionality in Structural Generalization

arXiv:2607.02307v1 Announce Type: new Abstract: Several SLOG test categories explicitly involve directional distinctions (modifier position shifts, argument extraction positions), yet AM-Parser, the p

researcharxiv-cs-cl

On the Sample Efficiency of Inverse Dynamics Models for Semi-Supervised Imitation Learning

arXiv:2602.02762v2 Announce Type: replace Abstract: Semi-supervised imitation learning (SSIL) consists in learning a policy from a small dataset of action-labeled trajectories and a much larger datase

On the Utility and Factual Reliability of Pruned Mixture-of-Experts Models in the Biomedical Domain

arXiv:2607.01444v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models offer inference speedups via selective activation but impose substantial memory requirements because the whole network

One Demonstration Is Enough for Real-World Robotic Reinforcement Learning

arXiv:2607.01651v1 Announce Type: new Abstract: Learning effective robot control policies on physical hardware is challenging due to costly data collection and the difficulty of reward specification.

safetyarxiv-cs-ro

One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective

model-releasesarxiv-cs-lg

arXiv:2607.02292v1 Announce Type: new Abstract: Neural quantum states (NQS) provide a flexible and scalable framework for approximating quantum many-body wavefunctions. Among NQS parameterizations, au

Online Resource Allocation with Continuous Random Consumption: Regret under Degeneracy

arXiv:2607.02196v1 Announce Type: new Abstract: We study online resource allocation when both rewards and consumption sizes may be continuously distributed. Requests arrive sequentially and must be ac

Online Safety Monitoring for LLMs

arXiv:2607.02510v1 Announce Type: new Abstract: Despite alignment training, LLMs remain prone to generating unsafe outputs at deployment time. Monitoring outputs online and raising an alarm when safet

OntoLearner: A Modular Python Library for Ontology Learning with Large Language Models

arXiv:2607.01977v1 Announce Type: new Abstract: Ontology learning (OL) aims to automatically construct structured knowledge models from text, yet progress remains fragmented across methods, domains, a

OpenSafeIntent: Evaluating Intent-Calibrated Safe Completion Across Dual-Use Prompt Sets

arXiv:2607.02047v1 Announce Type: cross Abstract: Safe completion requires models to provide useful assistance without enabling harm, but this behavior is difficult to evaluate with isolated prompts.

Agents

Ophiuchus: Incentivizing Tool-augmented 'Think with Images' for Joint Medical Segmentation, Understanding and Reasoning

arXiv:2512.14157v2 Announce Type: replace Abstract: Recent medical MLLMs have made significant progress in generating step-by-step textual reasoning chains. However, they still struggle with complex c

agentsarxiv-cs-ai

OPINE-World: Programmatic World Modeling with Ontology-error-Prioritized Interactive Exploration

arXiv:2607.01531v1 Announce Type: new Abstract: Learning how an environment behaves from interaction is central to building agents that adapt to unfamiliar tasks. World models learned with deep networ

Tutorials

Optimal Stabilizer Testing and Learning with Limited Quantum Memory

arXiv:2607.02444v1 Announce Type: cross Abstract: We study stabilizer state testing and learning with limited coherent quantum memory. Here an algorithm sequentially receives copies of an unknown n-qu

tutorialsarxiv-cs-lg

Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning

arXiv:2604.02091v2 Announce Type: replace-cross Abstract: Rerankers play a pivotal role in refining retrieval results for Retrieval-Augmented Generation. However, current reranking models are typicall

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

OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers

arXiv:2607.02461v1 Announce Type: cross Abstract: Diffusion transformers (DiTs) achieve state-of-the-art image and video generation, but their multi-step sampling and growing parameter count make infe

Overthink-Triggered Slowdown Attacks on LVLM-Based Robotic Systems

arXiv:2607.01518v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have been increasingly integrated into robotic systems. However, these models may exhibit overthinking behaviors,

safetyarxiv-cs-ro

Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond

arXiv:2607.02197v1 Announce Type: cross Abstract: The society and emerging risk-based regulatory frameworks for AI underscore the need for rigorous risk assessment to ensure safe and reliable AI syste

Applications

PACE: A Neuro-Symbolic Framework for Plausible and Actionable Counterfactual Explanations

arXiv:2607.01306v1 Announce Type: new Abstract: Counterfactual explanations explain machine learning predictions by identifying minimal input changes that would alter a model's decision. Although many

applicationsarxiv-cs-ai

PACE: A Proxy for Agentic Capability Evaluation

arXiv:2607.02032v1 Announce Type: new Abstract: Evaluating LLM agents on benchmarks like SWE-Bench and GAIA can be expensive, time-consuming, and requires complex infrastructure. A single evaluation c

PairCoder++: Pair Programming as a Universal Paradigm for Verified Code-Driven Multimodal and Structured-Artifact Generation

arXiv:2607.01883v1 Announce Type: new Abstract: Code is the medium through which large language models generate structured artifacts: charts, scientific figures, vector graphics, CAD models, 3D scenes

Parameter Golf: What Really Works?

arXiv:2607.01517v1 Announce Type: new Abstract: How far can a language model improve under a strict artifact budget? Parameter Golf posed this question as an open community challenge in which particip

PARTREP: Learning What to Repeat for Decoder-only LLMs

arXiv:2607.01792v1 Announce Type: new Abstract: While decoder-only LLMs excel at a vast array of natural language tasks, it suffers from an asymmetric information flow induced by causal attention: lat

researcharxiv-cs-cl

Path-level Hindsight Instructions for Semantic Exploration in Vision-Language Navigation

arXiv:2607.01754v1 Announce Type: new Abstract: On-policy exploration is a crucial component for training robust Vision-Language Navigation agents, as it exposes the policy to a broader state distribu

Path planning for unmanned naval surface vehicles

arXiv:2607.01631v1 Announce Type: new Abstract: There nowadays is a myriad of approaches to real-time avoidance of fixed obstacles for unmanned surface vehicles (USVs) and, to a lesser extent, also th

researcharxiv-cs-ro

Phonikud: Overcoming Phonetic Underspecification for Hebrew Text-To-Speech

arXiv:2506.12311v4 Announce Type: replace Abstract: Text-to-speech (TTS) for Modern Hebrew is challenged by the language's orthographic complexity, with existing solutions ignoring underspecified phon

PhysMani: Physics-principled 3D World Model for Dynamic Object Manipulation

arXiv:2607.01938v1 Announce Type: cross Abstract: Manipulating fast and dynamically moving targets in unstructured 3D environments remains challenging for embodied AI. Existing visual-language-action

Hardware

PixGS: Pixel-Space Diffusion for Direct 3D Gaussian Splat Generation

arXiv:2607.01803v1 Announce Type: cross Abstract: Recent advances in 3D content generation from text or images have achieved impressive results, yet view inconsistency from 2D generators and the scarc

hardwarearxiv-cs-ro

Playing 20 Question Game with Policy-Based Reinforcement Learning

arXiv:1808.07645v5 Announce Type: replace-cross Abstract: The 20 Questions (Q20) game is a well known game which encourages deductive reasoning and creativity. In the game, the answerer first thinks o

Pmeta-TLA: Backdoor Attacks for Speech Classification Models via Meta-Learning with Timbre Leakage Attack

arXiv:2607.01702v1 Announce Type: cross Abstract: Recently, speech classification methods have gained widespread adoption in intelligent gadgets. Current study indicates that backdoor attacks provide

Population-Based Multi-Objective Training of Discriminators for Semi-Supervised GANs

arXiv:2607.01907v1 Announce Type: cross Abstract: Semi-supervised generative adversarial networks (SSL-GANs) can exploit large unlabeled datasets while retaining a classifier in the discriminator, but

Population-Scale Segmentation of Penile Tissue in DIXON MRI using Deep Learning for Quantitative Phenotyping in Male Reproductive Health

model-releasesarxiv-cs-lg

arXiv:2607.02127v1 Announce Type: cross Abstract: Penile measurement is clinically relevant across male reproductive and urogenital health, including conditions such as micropenis, congenital and endo

Power Systems Agent Benchmark: Executable Evaluation of AI Agents in Electric Power Engineering

arXiv:2606.20950v2 Announce Type: replace Abstract: Executable evaluation -- checking the consequences of an agent's actions with a program rather than grading its prose -- has become a prominent way

PPTArena: A Benchmark for PowerPoint Editing

arXiv:2512.03042v3 Announce Type: replace-cross Abstract: We introduce PPTArena, a benchmark for PowerPoint editing that evaluates how agents modify real slides from natural-language instructions. Unl

Pre-Flight: A Benchmark for Evaluating Large Language Models on Aviation Operational Knowledge

arXiv:2607.01829v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for aviation business operations, from documentation and training generation to customer facing a

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

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

Predicting Early Stages Of Alzheimer's Disease And Identifying Key Biomarkers Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

arXiv:2607.02142v1 Announce Type: cross Abstract: Alzheimers disease (AD) is a brain disorder that develops slowly and mainly affects memory, thinking, language, and daily activities. It is one of the

Prediction Sets for Counterfactual Decisions: Coverage, Optimality, and Conformal Prediction

arXiv:2607.02206v1 Announce Type: cross Abstract: Predictions are increasingly used to guide high-stakes decisions, from treatment selection to policy making. To ensure reliability with imperfect pred