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arXiv:2609.01016v1 Announce Type: new Abstract: Current speech synthesis struggles with code-switching, which mixes a foreign language phrase into a primary language utterance, causing the phrase to b

local-aiarxiv-cs-cl

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Research

Physically Plausible Video Generation via Visual-Semantic Chain-of-Events Conditioning

DGX agent

arXiv:2609.00656v1 Announce Type: new Abstract: Physically Plausible Video Generation (PPVG) seeks to synthesize videos consistent with physical principles, yet remains challenging due to underspecifi

researcharxiv-cs-cv

2 Sept 2026

Physiological Information Reliability: Cross-Layer Adaptive Resource Allocation for Cardiovascular Sensing

arXiv:2609.00435v1 Announce Type: cross Abstract: Cardiovascular sensing systems must preserve clinically useful information despite signal degradation, wireless losses, energy constraints, and edge-c

enterprise-aiclaudebanking

Applications

Pictet rolls out Claude Code in banking and engineering

Human

Pictet rolled out Claude Code and Cowork to about 700 people; Anthropic reports selected prototype and compliance-task time savings.

Pix2Rep-v2: Data-Efficient Representation Learning for Dense Medical Imaging Applications

arXiv:2609.01427v1 Announce Type: new Abstract: Dense self-supervised learning (SSL) is a powerful paradigm for learning without annotations the local descriptors required to solve dense medical imagi

researcharxiv-cs-cv

Tutorials

Poisson-Gamma Dynamical Systems with Time-varying Transition Dynamics

arXiv:2609.00896v1 Announce Type: new Abstract: Bayesian methodologies for handling count-valued time series have gained prominence due to their ability to infer interpretable latent structures and to

tutorialsarxiv-cs-lg

Polarizable atomic multipoles for learning long-range electrostatics

arXiv:2605.05746v2 Announce Type: replace-cross Abstract: Long-range electrostatics and polarization remain central obstacles to extending machine learning interatomic potentials (MLIPs) to ionic, pol

Polish ModernBERT: The Long and Short of Polish Language Understanding

model-releasesarxiv-cs-cl

arXiv:2609.01379v1 Announce Type: new Abstract: Encoder-only Transformers remain effective for discriminative and representation-learning tasks, yet Polish encoders still largely rely on BERT/RoBERTa-

Agents

Polished but Unresolved: Identifying Late-Stage Pressure States in Long-Horizon Tool-Use Agents

arXiv:2609.00823v1 Announce Type: new Abstract: Long-horizon tool-use agents need not only to search and plan, but also to decide when to finalize. We study late-stage pressure states, in which an age

agentsarxiv-cs-ai

PopPert: Population-level Joint-Distribution Modeling for Single-Cell Perturbation Prediction

arXiv:2609.01357v1 Announce Type: cross Abstract: Predicting transcriptional responses to specific perturbations is critical for understanding cellular regulatory mechanisms and accelerating drug disc

Position Matters: Feature Inversion Attacks in ViT Split Inference with Token Reduction and Shuffling

arXiv:2609.01232v1 Announce Type: cross Abstract: Vision Transformers (ViTs) are increasingly used in split-inference systems, where edge devices transmit intermediate token representations to a remot

Position: Privacy Is a Claim, Not a Property of Synthetic Data

arXiv:2609.01273v1 Announce Type: new Abstract: Synthetic data has become a common component of machine learning research. While widely adopted, its use in privacy-sensitive contexts has quietly shift

Post-hoc Alignment of LLM-judges to Human Judgment Distribution

arXiv:2609.01073v1 Announce Type: new Abstract: The LLM-as-a-judge (LLMaJ) framework offers a cost-effective and reproducible solution for automatic evaluation. However, current evaluation practices t

safetyarxiv-cs-cl

Post-Training Science for Supervised Fine-Tuning

model-releasesarxiv-cs-cl

arXiv:2609.01244v1 Announce Type: cross Abstract: Every supervised fine-tuning run forces the same chain of decisions, such as learning rate, batch size, LoRA or full fine-tuning, how many epochs, whi

Potential-Guided Particle Steering for Negation-Constrained Dexterous Grasping

model-releasesarxiv-cs-cv

arXiv:2609.00555v1 Announce Type: cross Abstract: Language-driven dexterous grasp models, such as DextER, perform well when instructions specify where to grasp, but we find they fail systematically wh

Tutorials

Pre-carved Niches: The Formation Dynamics of Modular Task Partitions in Early LLM Training

arXiv:2609.01170v1 Announce Type: new Abstract: Large language models exhibit a modular internal organization that mirrors well-studied functional networks of the human brain, but how this organizatio

tutorialsarxiv-cs-lg

Tutorials

PredErase: Training-Free Object-and-Effect Removal with Predictive Latent Guidance

arXiv:2609.00956v1 Announce Type: new Abstract: Removing an object is not the same as filling its mask. Cast shadows and contact shading usually lie outside the user-provided instance mask M_obj, so a

tutorialsarxiv-cs-cv

Predicting Program Exit Code with LLMs and Programming Language Semantics

arXiv:2609.00579v1 Announce Type: cross Abstract: Large language models (LLMs) have shown proficiency in various software engineering tasks, such as code generation and translation. However, a key lim

Predicting Subsurface Abnormalities Growth using Physics-Informed Neural Networks

arXiv:2609.01417v1 Announce Type: new Abstract: The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data pred

Prediction-Assisted Pricing and Admission for LLM APIs with Stochastic Token Consumption

model-releasesarxiv-cs-lg

arXiv:2609.00710v1 Announce Type: cross Abstract: An LLM application often sells or internally allocates several service products: a small or premium model, a short or long token cap, and possibly mul

Applications

Prinz has been running legal benchmarks against AI systems and the latest models are very good... but cheaper/low reasoning models are not v…

applicationsethan-mollick--x

Prinz has been running legal benchmarks against AI systems and the latest models are very good... but cheaper/low reasoning models are not very good. So, how do you make sure your vendor selling an AI

Prior-Guided Implicit Neural Representations for Single-Subject Diffusion MRI Super-Resolution

arXiv:2609.00981v1 Announce Type: cross Abstract: Resolving complex fiber geometries in brain white matter requires high-resolution diffusion MRI at the cost of long acquisition times. This leads many

researcharxiv-cs-cv

Probabilistic Model Checking of Autoregressive Neural Sequence Models

arXiv:2609.00838v1 Announce Type: cross Abstract: Test-set accuracy is silent on two issues that matter when deploying autoregressive neural sequence models: how much probability mass the system under

Agents

Probabilistic Multi-Agent Aircraft Landing Time Prediction

arXiv:2512.08281v2 Announce Type: replace-cross Abstract: Accurate and reliable aircraft landing time prediction is essential for effective resource allocation in air traffic management. However, the

agentsarxiv-cs-lg

Probing Factual Knowledge Transfer with Training Data Interventions

arXiv:2609.01341v1 Announce Type: cross Abstract: Do multilingual language models transfer factual knowledge across languages during continued pretraining, or do they mostly recall facts learned direc

Process-Aware AI for Rainfall-Runoff Modeling: A Mass-Conserving Neural Framework with Hydrological Process Constraints

model-releasesarxiv-cs-lg

arXiv:2603.25093v2 Announce Type: replace Abstract: Machine learning models can achieve high predictive accuracy in hydrological applications but often lack physical interpretability. The Mass-Conserv

Prompt-Robust Language Models: Which Training Strategies Work?

arXiv:2609.01217v1 Announce Type: new Abstract: Despite their strong performance, large language models remain highly sensitive to prompt formulation. Prior work addresses this through refined data co

safetyarxiv-cs-ai

Provably Efficient Federated Reinforcement Learning with Linear Function Approximation and Logarithmic Communication Cost

arXiv:2609.00193v1 Announce Type: cross Abstract: We study federated online reinforcement learning with linear function approximation. While recent multi-agent reinforcement learning algorithms achiev

safetyarxiv-cs-ai

Provably Safe Sim-to-Real Transfer

arXiv:2609.01418v1 Announce Type: cross Abstract: To mitigate the sample complexity of real-world reinforcement learning (RL), a common practice is to first train a policy in a simulator, where sample

safetyarxiv-cs-ai

ProxPI: Proximal Prior Injection for Sampling-Based MPC under Learned-Prior Mismatch

arXiv:2609.00941v1 Announce Type: new Abstract: Combining learned policies with model predictive control can leverage learned task priors while retaining online adaptation to new objectives and constr

safetyarxiv-cs-ro

PSA: If you’re on the old Ollama Pro plan, don’t switch - ~67% LESS usage

Ollama has just announced, based on 'feedback', that they have switched to a credit model. If you're still on the old 20 Pro compute plan, DON'T SWITCH. I decided to calculate it before I risked click

model-releasesr-ollama

Pulled the trigger, RIP $6,279

model-releasesr-stablediffusion

(Paid 5,849 + tax, which came out to 6,279) TL;DR - Bought this 5090 prebuilt and I want to sanity check if I made the right decision and at the right time. Hey everyone. So I want to start off by say

Puppeteer: Object-Grounded Posture-Aware Co-Speech Gesture Generation

arXiv:2609.00369v1 Announce Type: new Abstract: Generating co-speech gestures that are temporally coherent, semantically aligned with speech, and grounded with surrounding objects remains challenging.

safetyarxiv-cs-cv

Hardware

PyDoseRT Proton: A GPU Pencil-Beam Engine with a Convolutional Residual-Correction Network for Fast Proton Dose Calculation

arXiv:2609.01018v1 Announce Type: cross Abstract: Architecture category. Hybrid method: a physics-based analytical pencil-beam (PB) dose engine followed by a 3-D convolutional residual-correction netw

hardwarearxiv-cs-cv

Industry

Q&A with METR researcher Ajeya Cotra on investigating the OpenAI-Hugging Face incident, AI agents involved in the hack deciding not to notify humans, and more (Dwarkesh Patel/Dwarkesh Podcast)

Dwarkesh Patel / Dwarkesh Podcast: Q&A with METR researcher Ajeya Cotra on investigating the OpenAI-Hugging Face incident, AI agents involved in the hack deciding not to notify humans, and more — “Thi

industrytechmeme

QILP-0: Constructing Observational Declarative Twins of Quantum Circuits

arXiv:2609.01049v1 Announce Type: new Abstract: This paper introduces QXymb, a general framework for constructing observational declarative twins of quantum circuits, and develops QILP-0, its first co

Hardware

QTEA: Ternary LLMs with Sparse Residual Salient Weight and By-Column Optimization

arXiv:2609.00224v1 Announce Type: cross Abstract: Weight-only post-training quantization (PTQ) can alleviate the computational burden of serving large language models (LLMs) at scale. However, existin

hardwarearxiv-cs-ai

Quad R9700 AI Pro with vLLM-Radiance easily reaching 17,6k PP

model-releasesr-localllama

https://preview.redd.it/74bmvel9b5nh1.png?width=1602&format=png&auto=webp&s=0d0c1adaa016a486ffd97c4c466e980dc611b139 I've only recently started looking deeper into vLLM after running llama.cpp for a g

Quantum Sparse Autoencoders for Q-Matrix Estimation in Cognitive Diagnosis

model-releasesarxiv-cs-lg

arXiv:2609.01537v1 Announce Type: new Abstract: Q-matrices play a central role in cognitive diagnosis within educational data mining (EDM), specifying which latent skills each assessment item requires

Quit While You're Ahead: Quit for Efficient Candidate Generation in Machine Translation Reranking

arXiv:2609.00588v1 Announce Type: new Abstract: Reranking methods, such as Minimum Bayes Risk (MBR) decoding and Quality Estimation (QE) reranking, are widely used in modern neural machine translation

researcharxiv-cs-cl

Quoting Rick Brewster

model-releasessimon-willison

Direct2D has always been the biggest hurdle for Paint.NET on WINE, and it's clear that it will never be completed enough for Paint.NET's use. And I can't just 'disable' the use of Direct2D. So, instea

Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2609.00111v1 Announce Type: new Abstract: We present Qwen-Drive-1.0, an initial step towards a vision-language foundation model for autonomous driving. Qwen-Drive-1.0 retains the architecture of

Qwen will be the king?

model-releasesr-localllama

Extended reasoning and post-training appear to be the keys used by DeepSeek, Qwen, and GLM to boost performance (leveraging higher token counts). And Qwen 4 hasn't even been released yet. Of course, w

Local Ai

Qwen3.8 Flash AP Quants

Quite surprised to be beating other high quality quants. It took a lot of benchmarking to get here and we are quite pleased with these, hope they are useful to the community. It required a modified wa

local-air-localllama

Qwen3.8-flash-next sees corruption everywhere

model-releasesr-localllama

Hi, I've noticed that the model often sees 'garbled text' in its context. Sometimes it declare that the tools instructions are corrupted, sometimes it is the content of some .md files, ora other files

Applications

🚀Qwen3.8-Max just got upgraded. Meet Qwen3.8-Max-0902! 2.4T parameters. 1M context tokens. Built for real world complexity. Further post tr…

🚀Qwen3.8-Max just got upgraded. Meet Qwen3.8-Max-0902! 2.4T parameters. 1M context tokens. Built for real world complexity. Further post trained on Coding & Cowork, Qwen3.8-Max-0902 now delivers stron

applicationsqwen--x

RadMatch: Auditable Radiology Report Evaluation via Finding-Level Matching

arXiv:2609.01470v1 Announce Type: new Abstract: As AI systems are increasingly used to draft radiology reports, reliably evaluating their clinical quality remains a critical challenge. Large language

safetyarxiv-cs-cv

Agents

RAPIDMap: Rapid Multi-Agent Pipeline for Interpretable Disaster Mapping from Satellite and Street-view Imagery

arXiv:2609.00046v1 Announce Type: cross Abstract: Rapid and reliable disaster mapping of impacted areas, damaged infrastructure, and affected populations is essential for emergency response and recove

agentsarxiv-cs-ai