All entries

Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback

arXiv:2605.26373v1 Announce Type: new Abstract: We study adversarial online learning with hidden-convex losses, i.e., nonconvex losses that become convex after a nonlinear reparameterization. Ghai, Lu

Safety

Only thing completely clear about the future of work is that Altman and Amodei will say whatever they think will drive up their IPOs.

DGX agent

Only thing completely clear about the future of work is that Altman and Amodei will say whatever they think will drive up their IPOs. Altman and Amodei have said for years that AI was so powerful that

safetygary-marcus--x

27 May 2026

Open Source Must Win - The Pope

Open Source Must Win - The Pope Today, among the goods that are universally intended for everyone, we must also include new forms of property, such as patents, algorithms, digital platforms, technolog

researchnous-research--x

Open-Weight LLM Fine-Tuning Defenses are Susceptible to Simple Attacks

arXiv:2605.26526v1 Announce Type: new Abstract: Recent defenses for safeguarding open-weight large language models (LLMs) are intended to prevent adversarial usage. Underlying these defenses is an ass

safetyarxiv-cs-lg

OpenAI announces partnerships to combat election misinformation, offering cybersecurity products to state officials and backing legislation to curb deepfakes (Maria Curi/Axios)

Maria Curi / Axios: OpenAI announces partnerships to combat election misinformation, offering cybersecurity products to state officials and backing legislation to curb deepfakes — OpenAI is announcing

safetytechmeme

Industry

OpenAI Foundation says it is committing an initial $250M for grants, partnerships, and direct work aimed at helping workers and economies navigate AI disruption (Reuters)

Reuters: OpenAI Foundation says it is committing an initial 250M for grants, partnerships, and direct work aimed at helping workers and economies navigate AI disruption — The non-profit that controls

industrytechmeme

Optimal Rates for Feasible Payoff Set Estimation in Games

arXiv:2602.04397v2 Announce Type: replace-cross Abstract: We study a setting in which two players play a (possibly approximate) Nash equilibrium of a bimatrix game, while a learner observes only their

agentsarxiv-cs-lg

Optimising Factual Consistency in Summarisation via Preference Learning from Multiple Imperfect Metrics

arXiv:2605.26840v1 Announce Type: new Abstract: Reinforcement learning with evaluation metrics as rewards is widely used to enhance specific capabilities of language models. However, for tasks such as

tutorialsarxiv-cs-cl

ORCA: An End-to-End Interactive Copilot for Optimized Root Cause Analysis

arXiv:2605.27022v1 Announce Type: new Abstract: Causal analysis is a crucial task in many domains, including manufacturing, social science, and medicine. However, despite recent progress, the conceptu

tutorialsarxiv-cs-ai

ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction and Behavioral Rationality in Operations Research

arXiv:2601.21008v3 Announce Type: replace-cross Abstract: Operations Research practitioners debug infeasible models through an iterative process: inspecting Irreducible Infeasible Subsystems ( IIS), i

OSMa-Bench++: Toward Open-Ended Benchmarking of Semantic Mapping for Manipulation with Prompt-Generated Synthetic Scenes

model-releasesarxiv-cs-cv

arXiv:2605.26831v1 Announce Type: new Abstract: Semantic mapping methods are increasingly used as intermediate scene representations for downstream robotic reasoning and manipulation, yet their evalua

Over-Alignment vs Over-Fitting: The Role of Feature Learning Strength in Generalization

arXiv:2602.00827v2 Announce Type: replace Abstract: Feature learning strength (FLS), i.e., the inverse of the effective output scaling of a model, plays a critical role in shaping the optimization dyn

safetyarxiv-cs-lg

Pair-In, Pair-Out: Latent Multi-Token Prediction for Efficient LLMs

arXiv:2605.27255v1 Announce Type: cross Abstract: Long chain-of-thought reasoning has made autoregressive decoding the dominant inference cost of modern large language models. Existing methods target

safetyarxiv-cs-ai

Palantir CEO Alex Karp goes after AI slop. The fight over AI “slop” is really a fight over whether software is performing or merely pretendi…

Palantir CEO Alex Karp goes after AI slop. The fight over AI “slop” is really a fight over whether software is performing or merely pretending. 'The appearance of software working is not software work

safetygary-marcus--x

PARE: Pruning and Adaptive Routing for Efficient Video Generation

arXiv:2605.27336v1 Announce Type: new Abstract: Video Diffusion Transformers (DiTs) generate high-quality videos but demand substantial compute due to wide blocks, deep architectures, and iterative sa

researcharxiv-cs-cv

Parsimonious Learning-Augmented Online Metric Matching

arXiv:2605.26886v1 Announce Type: cross Abstract: Learning-augmented algorithms have received significant attention in recent years, particularly in the context of online optimization. Motivated by th

ParsVoice: A Large-Scale Multi-Speaker Persian Speech Corpus for Text-to-Speech Synthesis

arXiv:2510.10774v3 Announce Type: replace-cross Abstract: Persian remains substantially underrepresented in open speech-text resources, limiting progress in multi-speaker text-to-speech (TTS), speech-

researcharxiv-cs-ai

Particle-Lund Multimodality in Jet Taggers

arXiv:2605.26821v1 Announce Type: cross Abstract: The Lund plane offers a physics-motivated, hierarchical representation of QCD radiation within jets, while transformer-based taggers have reached stat

PashtoTTS-Bench: automated screening for low-resource non-Latin-script text-to-speech

model-releasesarxiv-cs-cl

arXiv:2605.26978v1 Announce Type: new Abstract: Text-to-speech (TTS) evaluation for low-resource non-Latin-script languages can fail when it relies on a single ASR round-trip word error rate (WER). A

PaTAS: A Framework for Trust Propagation in Neural Networks Using Subjective Logic

arXiv:2511.20586v4 Announce Type: replace Abstract: Trustworthiness has become a key requirement for the deployment of artificial intelligence systems in safety-critical applications. Conventional eva

PATE-TabTransGAN: Differentially Private Synthetic Tabular Data Generation via Transformer-Based Student Discrimination

arXiv:2605.26802v1 Announce Type: new Abstract: Generating high-fidelity synthetic tabular data under formal differential privacy guarantees remains an open challenge. Methods that provide strong theo

per comments from @GergelyOrosz below i don’t think these data are compelling after all, and am deleting the OP

Gary Marcus deleted an original post after Gergely Orosz provided comments questioning the compelling nature of the data presented. The post appears to have been withdrawn due to critical feedback tha

safetygary-marcus--x

Periodic Topological Deep Learning for Polymer Design and Discovery

arXiv:2605.26833v1 Announce Type: cross Abstract: Polymers underpin applications across energy, healthcare, and materials science, yet their vast chemical space makes systematic discovery challenging.

PersianMedQA: Evaluating Large Language Models on a Persian-English Bilingual Medical Question Answering Benchmark

model-releasesarxiv-cs-cl

arXiv:2506.00250v4 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved remarkable performance on a wide range of Natural Language Processing (NLP) benchmarks, often surpassing

Local Ai

Persistent AI Agents in Academic Research: A Single-Investigator Implementation Case Study

arXiv:2605.26870v1 Announce Type: cross Abstract: Background: Large language models are typically evaluated as models, benchmarks, or short conversational episodes. Less is known about what happens wh

local-aiarxiv-cs-ai

PersLitEval: Fine-grained Benchmark and Evaluation of LLMs on Persian Literature Questions

model-releasesarxiv-cs-cl

arXiv:2605.27015v1 Announce Type: new Abstract: Despite impressive multilingual capabilities, large language models (LLMs) remain poorly evaluated on literary knowledge in non-English languages. We in

Persona Generators: Generating Diverse Synthetic Personas for Arbitrary Contexts

arXiv:2602.03545v2 Announce Type: replace Abstract: Evaluating AI systems that interact with humans requires understanding their behavior across diverse user populations, but collecting representative

agentsarxiv-cs-ai

Persona2Web: Benchmarking Personalized Web Agents for Contextual Reasoning with User History

arXiv:2602.17003v2 Announce Type: replace-cross Abstract: Large language models have advanced web agents, yet current agents lack personalization capabilities. Since users rarely specify every detail

Personalized Generative Models for Contextual Debiasing

arXiv:2605.26353v1 Announce Type: cross Abstract: Different visual patterns appear with different frequencies in the world: e.g., beach balls appear on sand more often than they do on a road. These st

tutorialsarxiv-cs-ai

Personalizing Embodied Multimodal Large Language Model Agents over Long-term User Interactions

arXiv:2605.26256v1 Announce Type: new Abstract: Multimodal large language model (MLLM)-based embodied agents have shown strong potential for solving complex tasks in physical environments. However, pe

agentsarxiv-cs-ai

Petraeus: Putin is the personification of evil. He wants to reassemble as much of the former Soviet Union or Russian Empire as he can, and h…

Petraeus: Putin is the personification of evil. He wants to reassemble as much of the former Soviet Union or Russian Empire as he can, and he does not believe Ukraine has a right to exist as an indepe

researchyann-lecun--x

Applications

Phase-Type Variational Autoencoders for Heavy-Tailed Data

arXiv:2603.01800v2 Announce Type: replace-cross Abstract: Heavy-tailed distributions are ubiquitous in real-world data, where rare but extreme events dominate risk and variability. However, standard V

applicationsarxiv-cs-ai

Local Ai

PhyGHT: Physics-Guided HyperGraph Transformer for Signal Purification at the HL-LHC

arXiv:2602.20475v2 Announce Type: replace-cross Abstract: The High-Luminosity Large Hadron Collider (HL-LHC) at CERN will produce unprecedented datasets capable of revealing fundamental properties of

local-aiarxiv-cs-lg

Applications

PhyPush: One Push is All You Need for Sensorless Physical Property Estimation with Physics-Guided Transformers

arXiv:2605.26284v1 Announce Type: new Abstract: Accurately estimating object mass and friction is fundamental to achieving reliable and adaptive robotic manipulation. Although interactive perception p

applicationsarxiv-cs-ro

Physics Informed Neural Networks for damped harmonic oscillator and Burger's Equation (with extrapolation analysis) [P]

researchr-machinelearning

Physics-informed neural networks (PINNs) are machine learning models that incorporate physical laws and equations as constraints during training to solve differential equations. This post likely discu

'PhyWorldBench': A Comprehensive Evaluation of Physical Realism in Text-to-Video Models

arXiv:2507.13428v3 Announce Type: replace-cross Abstract: Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurate

PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimization

arXiv:2507.16679v3 Announce Type: replace-cross Abstract: In-Context Learning has shown great potential for aligning Large Language Models (LLMs) with human values, helping reduce harmful outputs and

safetyarxiv-cs-ai

PIDM-DP: Physics-Informed Diffusion with Dormand-Prince Integration for Chaotic System Identification and State Reconstruction across Multiple Dynamical Regimes

model-releasesarxiv-cs-lg

arXiv:2605.26619v1 Announce Type: new Abstract: Reconstructing continuous state trajectories of chaotic dynamical systems from sparse, noisy observations remains a fundamental open problem in nonlinea

PILOT: A Data-Free Continual Learning Approach for Real-Time Semantic Segmentation via Boundary Guidance

arXiv:2605.27128v1 Announce Type: new Abstract: Real-time semantic segmentation models offer an excellent balance between accuracy and inference speed. However, deploying these models in dynamic real

tutorialsarxiv-cs-cv

PilotTTS: A Disciplined Modular Recipe for Competitive Speech Synthesis

arXiv:2605.27258v1 Announce Type: cross Abstract: Building state-of-the-art text-to-speech (TTS) systems typically demands millions of hours of proprietary data and complex multi-stage architectures,

PinPoint: Prompting with Informative Interior Points

arXiv:2605.26689v1 Announce Type: cross Abstract: Modern referring image segmentation pipelines couple a vision-language model (VLM) for grounding with a promptable segmenter such as the Segment Anyth

researcharxiv-cs-cl

PitchBench: Measuring Pitch Hearing in Audio-Language Models

arXiv:2605.26176v1 Announce Type: cross Abstract: Audio-language models (ALMs) are increasingly used in real-world applications that require understanding music, from music tutoring and transcription

PLAID: A Unified Data Model for Machine Learning on Heterogeneous Physics Simulations

arXiv:2505.02974v3 Announce Type: replace Abstract: Machine learning-based surrogate models have emerged as a powerful tool to accelerate simulation-driven scientific workflows, but their adoption is

Local Ai

Plan Then Action:High-Level Planning Guidance Reinforcement Learning for LLM Reasoning

arXiv:2510.01833v2 Announce Type: replace Abstract: Large language models (LLMs) demonstrate strong reasoning abilities via Chain-of-Thought (CoT), but their token-level generation encourages local de

local-aiarxiv-cs-ai

Planning Neural Dynamics with Lie Group Embedding through Supervised Projective Manifold Learning

arXiv:2605.26167v1 Announce Type: cross Abstract: We propose Lie group embedded dynamical neural networks (LieEDNN) and the corresponding learning algorithms based on gradient descent and metric proje

tutorialsarxiv-cs-ai

Plans for Evaluating Structured Generative Search Summaries

arXiv:2605.26400v1 Announce Type: cross Abstract: We propose a framework for evaluating structured generative search summaries that are placed atop organic web search results. A structured summary, ge

researcharxiv-cs-ai

PlayClass: Automated Play Behaviour Classification in Poultry

arXiv:2605.27304v1 Announce Type: new Abstract: Automated monitoring of animal welfare has largely targeted negative indicators, leaving positive welfare behaviours such as play underexplored. To addr

researcharxiv-cs-cv

PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design

arXiv:2605.26543v1 Announce Type: new Abstract: Polymer discovery is central to fields ranging from energy storage to biomedicine, but it is hindered by an astronomically large chemical design space a

agentsarxiv-cs-ai