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arXiv:2509.25926v2 Announce Type: replace-cross Abstract: Modern language models have enabled the development of agentic systems that achieve strong performance on reasoning-intensive tasks. Unfortuna

agentsarxiv-cs-lg

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Preventing Rank Collapse in Federated Low-Rank Adaptation with Client Heterogeneity

DGX agent

arXiv:2602.13486v2 Announce Type: replace-cross Abstract: Federated low-rank adaptation (FedLoRA) has facilitated communication-efficient and privacy-preserving fine-tuning of foundation models for do

local-aiarxiv-cs-ai

12 May 2026

Price of Quality: Sufficient Conditions for Sparse Recovery using Mixed-Quality Data

arXiv:2605.10713v1 Announce Type: cross Abstract: We study sparse recovery when observations come from mixed-quality sources: a small collection of high-quality measurements with small noise variance

PRIM: Meta-Learned Bayesian Root Cause Analysis

arXiv:2605.08786v1 Announce Type: new Abstract: Root cause analysis (RCA) in complex systems is challenging due to error propagation across multiple variables, the need for structural causal knowledge

Primal-Dual Guided Decoding for Constrained Discrete Diffusion

arXiv:2605.09749v1 Announce Type: new Abstract: Discrete diffusion models generate structured sequences by progressively unmasking tokens, but enforcing global property constraints during generation r

PrimeKG-CL: A Continual Graph Learning Benchmark on Evolving Biomedical Knowledge Graphs

arXiv:2605.10529v1 Announce Type: new Abstract: Biomedical knowledge graphs underwrite drug repurposing and clinical decision support, yet the upstream ontologies they depend on update on independent

Priming: Hybrid State Space Models From Pre-trained Transformers

arXiv:2605.08301v1 Announce Type: cross Abstract: Hybrid State-Space models combine Attention with recurrent State-Space Model (SSM) layers, balancing eidetic memory from Attention with compressed fad

Princeton faculty votes to require proctoring in all in-person exams starting this summer, reversing an 1893 policy amid concerns about AI-fueled cheating (Douglas Belkin/Wall Street Journal)

Douglas Belkin / Wall Street Journal: Princeton faculty votes to require proctoring in all in-person exams starting this summer, reversing an 1893 policy amid concerns about AI-fueled cheating — The c

safetytechmeme

Priority-Driven Control and Communication in Decentralized Multi-Agent Systems via Reinforcement Learning

arXiv:2605.10482v1 Announce Type: cross Abstract: Event-triggered control provides a mechanism for avoiding excessive use of constrained communication bandwidth in networked multi-agent systems. Howev

Tutorials

PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models

arXiv:2605.10925v1 Announce Type: new Abstract: Large-scale pretraining has made Vision-Language-Action (VLA) models promising foundations for generalist robot manipulation, yet adapting them to downs

tutorialsarxiv-cs-ro

Agents

PRISM: Fast Online LLM Serving via Scheduling-Memory Co-design

arXiv:2605.08581v1 Announce Type: new Abstract: Modern online large language model (LLM) services, such as Retrieval-Augmented Generation (RAG) and agent systems, increasingly expose two prominent cha

agentsarxiv-cs-lg

PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelines

arXiv:2605.10614v1 Announce Type: new Abstract: Multi-agent LLM systems introduce a security risk in which sensitive information accessed by one agent can propagate through shared context and reappear

Privacy Auditing Synthetic Data Release through Local Likelihood Attacks

arXiv:2508.21146v2 Announce Type: replace Abstract: Auditing the privacy leakage of synthetic data is an important but unresolved problem. Existing privacy auditing frameworks for synthetic data rely

Privacy-Aware Video Anomaly Detection through Orthogonal Subspace Projection

arXiv:2605.08651v1 Announce Type: cross Abstract: Video anomaly detection (VAD) systems often prioritize accuracy while overlooking privacy concerns, limiting their suitability for real-world deployme

Privacy-Preserving Distributed Learning in IoT Systems: A Unified Threat Model and Evaluation Framework

arXiv:2605.09232v1 Announce Type: cross Abstract: The increasing deployment of Internet-of-Things (IoT) devices has accelerated the use of distributed learning frameworks, where data remains local whi

local-aiarxiv-cs-lg

Privacy-Preserving Federated Learning: Integrating Zero-Knowledge Proofs in Scalable Distributed Architectures

arXiv:2605.08152v1 Announce Type: cross Abstract: The intersection of Artificial Intelligence (AI) and distributed systems has given rise to Federated Learning (FL), a paradigm that enables decentrali

local-aiarxiv-cs-ai

Private Vertical Federated Inference for Time-Series

arXiv:2605.08343v1 Announce Type: new Abstract: Institutions may benefit from collaborative inference on time-series data. In settings where privacy is necessary, multi-party computation (MPC) is a st

ProactBench: Beyond What The User Asked For

arXiv:2605.09228v1 Announce Type: cross Abstract: Most LLM benchmarks score how well a model responds to explicit requests. They leave unmeasured a different conversational ability: noticing and actin

Probability-Flow Distillation: Exact Wasserstein Gradient Flow for High-Fidelity 3D Generation

arXiv:2605.09071v1 Announce Type: new Abstract: Score Distillation Sampling (SDS) and its variants have been widely used for text-to-3D generation by distilling 2D image diffusion priors. However, the

researcharxiv-cs-cv

Probing Cross-modal Information Hubs in Audio-Visual LLMs

arXiv:2605.10815v1 Announce Type: new Abstract: Audio-visual large language models (AVLLMs) have recently emerged as a powerful architecture capable of jointly reasoning over audio, visual, and textua

Probing Routing-Conditional Calibration in Attention-Residual Transformers

arXiv:2605.09850v1 Announce Type: cross Abstract: Post-hoc calibration is usually evaluated as a function of logits or softmax confidence alone, even as routing-augmented architectures increasingly ac

Probing the Critical Point (CritPt) of AI Reasoning: a Frontier Physics Research Benchmark

arXiv:2509.26574v4 Announce Type: replace Abstract: While large language models (LLMs) with reasoning capabilities are progressing rapidly on high-school math competitions and coding, can they reason

Probing the Impact of Scale on Data-Efficient, Generalist Transformer World Models for Atari

arXiv:2605.08578v1 Announce Type: cross Abstract: Developing generalist systems that retain human-like data efficiency is a central challenge. While world models (WMs) offer a promising path, existing

Process Matters more than Output for Distinguishing Humans from Machines

arXiv:2605.06524v2 Announce Type: replace Abstract: Reliable human-machine discrimination is becoming increasingly important as large language models and autonomous agents are deployed in online setti

ProcVLM: Learning Procedure-Grounded Progress Rewards for Robotic Manipulation

arXiv:2605.08774v1 Announce Type: cross Abstract: Long-horizon robotic manipulation requires dense feedback that reflects how a task advances through its procedural stages, not merely whether the fina

safetyarxiv-cs-lg

ProDG: Prototypes for Data-Free Generative Post-Hoc Explainability

arXiv:2605.08858v1 Announce Type: new Abstract: Ante-hoc interpretability methods based on prototypes provide highly accurate explanations by utilizing the intuitive 'this looks like that' reasoning p

researcharxiv-cs-cv

Product-of-Gaussian-Mixture Diffusion Models for Joint Nonlinear MRI Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.10629v1 Announce Type: new Abstract: Recently, diffusion models have attracted considerable attention for magnetic resonance image reconstruction due to their high sample quality. However,

Progressive Photorealistic Simplification

arXiv:2605.10409v1 Announce Type: new Abstract: Existing image simplification techniques often rely on Non-Photorealistic Rendering (NPR), transforming photographs into stylized sketches, cartoons, or

researcharxiv-cs-cv

Projection-Free Functional Constrained Optimization for Risk Aversion and Sparsity Control

arXiv:2210.05108v2 Announce Type: replace-cross Abstract: We study projection-free methods for functional constrained optimization with convex or smooth nonconvex objectives. Such problems arise in ap

Industry

Prompt - 'photo is from year [Write a random year here] ], it was called 'a few seconds before happiness' ......... wtf I used the year 1822 , what was going on then?

A Reddit discussion from r/ChatGPT where a user shared a prompt experiment asking an AI to generate a photo from a random year with the title 'a few seconds before happiness,' and then questioned what

industryr-chatgpt

Prompt-Activation Duality: Improving Activation Steering via Attention-Level Interventions

arXiv:2605.10664v1 Announce Type: cross Abstract: Activation steering controls language model behavior by adding directions to internal representations at inference time, but standard residual-stream

Prompt Estimation from Prototypes for Federated Prompt Tuning of Vision Transformers

model-releasesarxiv-cs-cv

arXiv:2510.25372v2 Announce Type: replace Abstract: Visual Prompt Tuning (VPT) of pre-trained Vision Transformers (ViTs) has proven highly effective as a parameter-efficient fine-tuning technique for

PromptDx: Differentiable Prompt Tuning for Multimodal In-Context Alzheimer's Diagnosis

arXiv:2605.08585v1 Announce Type: cross Abstract: Deep learning models in medical imaging typically operate as parametric memory, diagnosing patients by recalling fixed knowledge learned during traini

PromptGuard: Soft Prompt-Guided Unsafe Content Moderation for Text-to-Image Models

arXiv:2501.03544v5 Announce Type: replace-cross Abstract: Recent text-to-image (T2I) models have exhibited remarkable performance in generating high-quality images from text descriptions. However, the

Prophecy: Inferring Formal Properties from Neuron Activations

arXiv:2509.21677v2 Announce Type: replace Abstract: We present Prophecy, a tool for automatically inferring formal properties of feed-forward neural networks. Prophecy is based on the observation that

Applications

Prospective Compression in Human Abstraction Learning

arXiv:2605.09985v1 Announce Type: new Abstract: A core challenge in program synthesis is online library learning: the incremental acquisition of reusable abstractions under uncertainty about future ta

applicationsarxiv-cs-ai

ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design

arXiv:2605.10189v1 Announce Type: cross Abstract: Designing proteins with desired functions or properties represents a core goal in synthetic biology and drug discovery. Recent advances in protein lan

Provable Anytime Ensemble Sampling Algorithms in Nonlinear Contextual Bandits

arXiv:2510.10730v2 Announce Type: replace-cross Abstract: We provide a unified algorithmic framework for ensemble sampling in nonlinear contextual bandits and develop corresponding regret bounds for t

Provable Sparse Inversion and Token Relabel Enhanced One-shot Federated Learning with ViTs

arXiv:2605.10748v1 Announce Type: cross Abstract: One-Shot Federated Learning, where a central server learns a global model in a single communication round, has emerged as a promising paradigm. Howeve

Tutorials

PruneTIR: Inference-Time Tool Call Pruning for Effective yet Efficient Tool-Integrated Reasoning

arXiv:2605.09931v1 Announce Type: cross Abstract: Tool-integrated reasoning (TIR) enables large language models (LLMs) to enhance their capabilities by interacting with external tools, such as code in

tutorialsarxiv-cs-ai

Pseudo-Deliberation in Language Models: When Reasoning Fails to Align Values and Actions

arXiv:2605.09893v1 Announce Type: cross Abstract: Large language models (LLMs) are often evaluated based on their stated values, yet these do not reliably translate into their actions, a discrepancy t

PumpSense: Real-Time Detection and Target Extraction of Crypto Pump-and-Dumps on Telegram

model-releasesarxiv-cs-cl

arXiv:2605.09431v1 Announce Type: new Abstract: Cryptocurrency pump-and-dump schemes coordinated via Telegram threaten market integrity. However, existing research addressing this specific threat has

PYTHALAB-MERA: Validation-Grounded Memory, Retrieval, and Acceptance Control for Frozen-LLM Coding Agents

arXiv:2605.08468v1 Announce Type: cross Abstract: Local LLM-based coding agents increasingly work in settings where correctness is earned through execution feedback, persistent state, and bounded repa

local-aiarxiv-cs-ai

Q-learning with Adjoint Matching

arXiv:2601.14234v3 Announce Type: replace-cross Abstract: We propose Q-learning with Adjoint Matching (QAM), a novel TD-based reinforcement learning (RL) algorithm that tackles a long-standing challen

QM-ToT: A Medical Tree of Thoughts Reasoning Framework for Quantized Model

model-releasesarxiv-cs-cl

arXiv:2504.12334v2 Announce Type: replace Abstract: Large language models (LLMs) face significant challenges in specialized biomedical tasks due to the inherent complexity of medical reasoning and the

QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space

arXiv:2605.10458v1 Announce Type: new Abstract: Atomic properties such as partial charges or multipoles encode chemically meaningful information that can inform downstream molecular property predictio

Hardware

Qualcomm closed down 11.46% on Tuesday as chip stocks pull back from record AI-driven rally; Intel closed down 6.82%, Sandisk dropped 6%, and Micron 3.61% (Samantha Subin/CNBC)

Samantha Subin / CNBC: Qualcomm closed down 11.46% on Tuesday as chip stocks pull back from record AI-driven rally; Intel closed down 6.82%, Sandisk dropped 6%, and Micron 3.61% — Chip stocks dropped

hardwaretechmeme

Quantifying Concentration Phenomena of Mean-Field Transformers in the Low-Temperature Regime

arXiv:2605.10931v1 Announce Type: cross Abstract: Transformers with self-attention modules as their core components have become an integral architecture in modern large language and foundation models.