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PhoneWorld: Scaling Phone-Use Agent Environments

arXiv:2605.29486v1 Announce Type: cross Abstract: A central bottleneck for phone-use agents is that controllable, reproducible environments covering real mobile behavior are hard to build at scale. Ex

Agents

PhyGenHOI: Physically-Aware 4D Generation of Dynamic Human-Object Interactions

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DGX agent

arXiv:2605.30268v1 Announce Type: cross Abstract: We address the task of generating physically accurate and visually faithful 4D Human-Object Interaction (HOI). Given a static 3D human and target obje

agentsarxiv-cs-ai

29 May 2026

Physics Is All You Need? A Case Study in Physicist-Supervised AI Development of Scientific Software

arXiv:2605.30353v1 Announce Type: new Abstract: Are AI agents tools, co-authors, or researchers? We present a quantified case study (N=1): a physicist supervising an AI coding agent (Claude Code, Sonn

Plan, Don't Pose: Long Composite Motion Generation with Text-Aligned BFM

arXiv:2605.29906v1 Announce Type: new Abstract: Text-to-motion (T2M) generation has broad applications in character animation, virtual avatars, and human-robot interaction. Existing methods typically

Planning with the Views via Scene Self-Exploration

arXiv:2605.29563v1 Announce Type: new Abstract: Can VLMs predict how each camera move changes the view, and plan many such moves ahead? We call this capability view planning, requiring (1)understandin

Pocket-Dentist: On-Device Dental Image Understanding via Efficient Multimodal Large Language Models

arXiv:2605.29299v1 Announce Type: cross Abstract: Evaluations of dental vision-language models remain fragmented across datasets, task definitions and metrics, and often ignore their computational cos

PokerSkill: LLMs Can Play Expert-Level Poker without Training or Solvers

arXiv:2605.30094v1 Announce Type: new Abstract: Poker is a landmark challenge for artificial intelligence. The dominant approach relies on equilibrium solvers built on counterfactual regret minimizati

Position: Stop Chasing the C-index when Evaluating Survival Analysis Models

arXiv:2506.02075v2 Announce Type: replace-cross Abstract: The current state of evaluation in survival analysis is plagued by the persistent use of evaluation metrics in ways that are misaligned with t

Applications

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning

arXiv:2506.08354v2 Announce Type: replace-cross Abstract: This position paper argues that text embedding research should move beyond surface meaning and embrace implicit semantics as a central modelin

applicationsarxiv-cs-ai

Tutorials

Practical Insights on Grasp Strategies for Mobile Manipulation in the Wild

arXiv:2504.12512v2 Announce Type: replace Abstract: Mobile manipulation robots are continuously advancing, with their grasping capabilities rapidly progressing. However, there are still significant ga

tutorialsarxiv-cs-ro

Practitioner Beliefs and Behaviors in AI-Enhanced Education: DOT Framework Survey Evidence

arXiv:2605.29041v1 Announce Type: new Abstract: This study reports findings from a cross-sectional survey (n = 72) of higher education practitioners examining beliefs, behaviors, and institutional con

PRAIB: Peer Review AI Benchmark of Behaviour of LLM-Assisted Reviewing

arXiv:2605.29815v1 Announce Type: new Abstract: The growing number of submitted papers has motivated the exploration of Large Language Models (LLMs) as a means to support and augment the peer review p

Pre-Registering the Detectable Effect: A Paired-MDE Budget for 4-bit Quantization Benchmarks, with a Pilot Audit

arXiv:2605.28873v1 Announce Type: new Abstract: This is a planning-method note with an unpaired pilot audit. We adapt the classical paired-binary sample-size calculation (Miettinen, 1968) to quantizat

Predicting Causal Effects from Natural Language Queries using Structured Representations

arXiv:2605.29631v1 Announce Type: cross Abstract: Randomized controlled trials are a cornerstone of medicine and the social sciences as they enable reliable estimates of causal effects. However, they

Applications

Prediction-Powered Inference Across Many Tasks for AI Evaluation & Social Science Research

arXiv:2605.29249v1 Announce Type: cross Abstract: Many applications require statistically valid inference across many related tasks, while using only a handful of high-quality labels per hypothesis. I

applicationsarxiv-cs-lg

Prescribe-then-Select: Adaptive Policy Selection for Contextual Stochastic Optimization

arXiv:2509.08194v2 Announce Type: replace Abstract: We address the problem of policy selection in contextual stochastic optimization (CSO), where covariates are available as contextual information and

Prioritize the Process, Not Just the Outcome: Rewarding Latent Thought Trajectories Improves Reasoning in Looped Language Models

arXiv:2602.10520v3 Announce Type: replace Abstract: Looped Language Models (LoopLMs) perform multi-step latent reasoning prior to token generation and outperform conventional LLMs on reasoning benchma

Tutorials

PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation

arXiv:2605.28867v1 Announce Type: cross Abstract: Generating high-quality time-series data is challenging because real-world signals often exhibit multimodal patterns and multiscale dynamics, includin

tutorialsarxiv-cs-ai

Privacy-Enhanced Zero-Order Federated Learning via xMK-CKKS over Wireless Channels

arXiv:2605.30123v1 Announce Type: cross Abstract: Homomorphic encryption (HE) enables privacy-preserving aggregation in federated learning (FL) by allowing the server to operate on encrypted data with

researcharxiv-cs-lg

PRO-CUA: Process-Reward Optimization for Computer Use Agents

arXiv:2605.29119v1 Announce Type: new Abstract: Computer use agents (CUAs) have shown strong potential for automating complex digital workflows, yet their training remains constrained by costly live e

Probabilistic bias adjustment of seasonal forecasts using generative machine learning: A case study of Arctic sea ice predictions

arXiv:2605.29172v1 Announce Type: new Abstract: Seasonal climate predictions support planning and risk management by offering early information of the most likely-to-occur climate conditions in the co

Procedural Pretraining: Warming Up Language Models with Abstract Data

arXiv:2601.21725v2 Announce Type: replace Abstract: Pretraining language models directly on web-scale corpora is the de facto paradigm. We study an alternative where the model is initially exposed to

researcharxiv-cs-cl

Projectional Decoding: Towards Semantic-Aware LLM Generation

arXiv:2605.30054v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate software artifacts across many software engineering (SE) tasks, yet ensuring the semant

researcharxiv-cs-ai

ProjectionBench: Evaluating Scientific Hypothesis Generation in LLMs Under Progressive Information Disclosure

arXiv:2605.30284v1 Announce Type: new Abstract: Scientific discovery is an inherently creative and uncertain process, requiring reasoning beyond the recall of known knowledge. While many benchmarks ha

Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation

arXiv:2310.14161v2 Announce Type: replace Abstract: Machine learning has been successfully applied to improve the efficiency of Mixed-Integer Linear Programming (MILP) solvers. However, the learning-b

Prompt-Level Reward Specifications for Open-Ended Post-Training

arXiv:2605.29275v1 Announce Type: new Abstract: Open-ended post-training benefits from rewards that make prompt-specific success conditions explicit, rather than relying only on post-hoc scalar scores

local-aiarxiv-cs-cl

PROTOCOL: Late Interaction Retrieval for Protein Homolog Search

arXiv:2605.29158v1 Announce Type: new Abstract: Protein homology search underlies function annotation, structure prediction, and evolutionary analysis, but remains challenging in the 'twilight zone,'

local-aiarxiv-cs-lg

Provable Affine Identifiability of Nonlinear CCA under Latent Distributional Priors

arXiv:2510.04758v2 Announce Type: replace Abstract: In this work, we establish the sufficient conditions under which nonlinear Canonical Correlation Analysis (CCA) recovers ground-truth latent factors

researcharxiv-cs-lg

Provably Secure Agent Guardrail

arXiv:2605.29251v1 Announce Type: new Abstract: As large language models transition from bounded generative engines to agents with expansive execution privileges, AI going out of control precipitates

PTCG-Bench: Can LLM Agents Master Pokemon Trading Card Game?

arXiv:2605.29653v1 Announce Type: new Abstract: Given a strategically complex board game, human players can quickly learn to devise strategies after playing a few rounds. Autonomous agents require sim

Pushing the Limits of Block Rotations in Post-Training Quantization

arXiv:2601.22347v2 Announce Type: replace-cross Abstract: Recent post-training quantization (PTQ) methods have adopted block rotations to diffuse outliers prior to rounding. While this reduces the ove

researcharxiv-cs-ai

PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data

arXiv:2508.15180v3 Announce Type: replace Abstract: High-quality mathematical and logical datasets with verifiable answers are essential for strengthening the reasoning capabilities of large language

Q-ANCHOR: Federated Quantum Learning with ZNE-guided Correction

arXiv:2605.30075v1 Announce Type: new Abstract: Quantum Federated Learning (QFL) offers a promising framework to train quantum models across distributed clients while keeping data strictly local. Due

local-aiarxiv-cs-lg

Quantifying and Optimizing Simplicity via Polynomial Representations

arXiv:2605.29823v1 Announce Type: new Abstract: Deep networks often exhibit a preference for 'simple' solutions, and such a simplicity bias is widely believed to play a key role in generalization. Yet

Quantum-Enhanced Adversarial Robustness in Artificial Intelligence

arXiv:2605.28899v1 Announce Type: cross Abstract: Artificial Intelligence has achieved remarkable success across diverse application domains. However, its vulnerability to adversarial attacks poses si

Quotient DAGs for Off-Policy Evaluation:Forward-Flow Importance Sampling and Exact Slate Propensities

arXiv:2605.29500v1 Announce Type: cross Abstract: Off-policy evaluation estimates how a target policy would perform using data collected by a different behavior policy, which is crucial when online te

Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

arXiv:2605.30280v1 Announce Type: cross Abstract: Embodied intelligence is often studied through specialized models for individual tasks such as manipulation or navigation, resulting in fragmented cap

RadioFormer3D: Weakly Supervised 3D Radio Map Estimation in Low-Altitude Airspace via Generative Modeling

arXiv:2605.29538v1 Announce Type: new Abstract: With the emergence of wireless applications in three-dimensional environments, such as the low-altitude airspace and 3D heterogeneous networks, radio ma

local-aiarxiv-cs-cv

RAISE: RAG Design as an Architecture Search Problem

arXiv:2605.30029v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems expose numerous design choices spanning query rewriting, chunking, retrieval depth, reranking, and context

Rare Event Analysis of Large Language Models

arXiv:2602.06791v2 Announce Type: replace Abstract: Being probabilistic models, during inference large language models (LLMs) display rare events: behaviour that is far from typical but highly signifi

researcharxiv-cs-lg

ReactBench: A Cause-Driven Benchmark for Multimodal Hallucination via Systematic Evaluation

model-releasesarxiv-cs-cv

arXiv:2605.29579v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) have achieved rapid progress in vision-language understanding, they remain prone to multimodal hallucinat

Agents

Real-rootedness of the Poincare polynomials of overline{mathcal M}_{0,n}: an AI-assisted proof

arXiv:2605.29151v1 Announce Type: cross Abstract: We prove real-rootedness for the Poincare polynomial [ P_n(t)=sum_{i=0}^{n-3} im H^{2i}(overline{mathcal M}_{0,n};Q)t^i ] of the Deligne--Mumford modu

agentsarxiv-cs-ai

Real-Time Retargeting Using Controllability Boundary for Chandrayaan-3 Lunar Landing

arXiv:2605.29412v1 Announce Type: cross Abstract: This paper presents the real-time retargeting guidance policy developed for the Chandrayaan-3 lunar landing mission. The baseline guidance generates a

Realistic honeypot evaluations for scheming propensity

arXiv:2605.29729v1 Announce Type: new Abstract: We introduce scheming honeypot evaluations, a framework for testing whether models will pursue instrumental goals if given the opportunity. Our scheming

ReasonBreak: Probing Vulnerabilities in Reasoning-Enabled Vision-Language-Action Models for Autonomous Driving

arXiv:2605.29114v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models with integrated reasoning have been proposed for end-to-end autonomous driving, assuming a tight coupling between

Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs

arXiv:2602.02909v2 Announce Type: replace Abstract: Inference-time scaling via chain-of-thought (CoT) reasoning is a major driver of state-of-the-art LLM performance, but it comes with substantial lat

researcharxiv-cs-ai

Reasoning and Tool-use Compete in Agentic RL:From Quantifying Interference to Disentangled Tuning

arXiv:2602.00994v2 Announce Type: replace Abstract: Agentic Reinforcement Learning (ARL) trains large language models to interleave reasoning with external tool execution to solve complex tasks. Most

Reasoning-preserved Efficient Distillation of Large Language Models via Activation-aware Initialization

model-releasesarxiv-cs-cl

arXiv:2605.29327v1 Announce Type: new Abstract: Efficient Distillation (EDistill) compresses large language models (LLMs) by structured pruning parameters and tuning lightweight modules with high trai