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Open Vocabulary Word Recognition From Transcribed Bangla Texts

arXiv:2610.01134v1 Announce Type: new Abstract: An optical character recognition (OCR) can scan a paper and extract text using technology, making people's jobs easier. While various OCR systems are av

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Agents

OpenAI says it learned this week that its AI agent hacked Australia's NSW state government in June, following a similar hack of Australia's federal government (Henry Belot/The Guardian)

DGX agent

Henry Belot / The Guardian: OpenAI says it learned this week that its AI agent hacked Australia's NSW state government in June, following a similar hack of Australia's federal government — Attack acce

agentstechmeme

2 Oct 2026

Industry

OpenAI upgraded my plan from plus to pro without my consent

I've been on Plus for over a year and have never once agreed to an upgrade to Pro, yet I've now been charged for it twice. This is ridiculous. Plenty of other users have been reporting the exact same

industryr-chatgpt

Agents

OpenAI’s Dot agent is enterprise software that can also order your dinner

It's a tale as old as last week: OpenAI's new agent platform, called Dots, is full of cute little guys who can do your bidding. But unlike the ultra-approachable Meta Muse, Dots feel very much like us

agentsthe-verge-ai

OpenMTB-Audit: Exposing Over-Refusal and Clinical Expert Perspectives in LLM-Based Molecular Tumor Board Safety Evaluation

arXiv:2610.01497v1 Announce Type: new Abstract: Molecular tumor boards integrate genomic findings, clinical context, and therapeutic evidence to support precision oncology. As AI enters this workflow,

OpenSpace Lab Solution to the IROS 2026 Indoor Exploration Competition

model-releasesarxiv-cs-ro

arXiv:2610.01505v1 Announce Type: new Abstract: This report presents the extbf{OpenSpace Lab}'s solution to the Competition on Intelligent Information Gathering for Single and Multi-Robot Systems Work

Optimal Centered Active Excitation in Linear System Identification

arXiv:2604.05518v2 Announce Type: replace-cross Abstract: We propose an active learning algorithm for linear system identification with optimal centered noise excitation. Notably, our algorithm, based

Optimal Momentum Methods for Stochastic Multilevel Compositional Optimization

arXiv:2610.01572v1 Announce Type: cross Abstract: This paper investigates stochastic multi-level optimization where the objective is a nested composition of several smooth non-convex functions. We ass

Optimal Stochastic Bilevel Optimization with First-Order Oracles

arXiv:2610.01843v1 Announce Type: cross Abstract: We study nonconvex--strongly-convex bilevel optimization under a stochastic first-order oracle. We introduce MRT-FD, a single-loop first-order method

Optimal Transport Meets Reinforcement Learning: A Survey

arXiv:2610.01413v1 Announce Type: cross Abstract: Reinforcement learning (RL) algorithms frequently compare probability distributions, such as state visitation distributions induced by policies and ex

Optimal Transport Reweighting for Robust Learning under Spurious Correlations and Label Noise

arXiv:2610.01028v1 Announce Type: cross Abstract: Machine learning models often suffer performance degradation under subpopulation shift, particularly when spurious correlations cause models to rely o

safetyarxiv-cs-ai

OptimusMesh: Compact Autoregressive Mesh Generation from Point Clouds via Sparse Latent Pivots

arXiv:2610.01148v1 Announce Type: new Abstract: Generating compact and geometrically faithful 3D meshes directly from point clouds remains a fundamental challenge. Point clouds are unordered and spars

OR for AI That Does OR: Routing LLMs up the Escalator inside the OSCAR Framework

arXiv:2610.00912v1 Announce Type: new Abstract: Large language models can translate business descriptions into optimization models, but executable code may misrepresent constraints or objectives. A so

Hardware

ORBIT-FMIB: Tracking Order-Resolved Epistatic Information Through ESM-2

arXiv:2610.00672v1 Announce Type: new Abstract: Protein foundation models support mutation-effect and structural prediction, but predictive performance alone does not reveal which forms of biological

hardwarearxiv-cs-lg

Agents

OrbitTAMP: Grounding Language Models for Task and Motion Planning in Spacecraft Rendezvous

arXiv:2610.01093v1 Announce Type: cross Abstract: Spacecraft rendezvous and proximity operations (RPO) are currently planned through an expertise-intensive process in which engineers translate high-le

agentsarxiv-cs-ai

Outer Diversity of Condorcet Domains

arXiv:2610.00720v1 Announce Type: cross Abstract: A Condorcet domain is a set of rankings over a given candidate set, such that every election that consists only of (an odd number of) votes from the d

Overcoming Kernel Redundancy for Scaling Logic Gate Networks

arXiv:2610.01069v1 Announce Type: new Abstract: Differentiable logic gate networks, which operate using only logic gates, have recently attracted attention as an efficient alternative to conventional

PACE: Persona Adaptation through Conversational Elicitation in Human-Robot Interaction

arXiv:2607.15579v3 Announce Type: replace Abstract: Equipping humanoid robots with coherent and adaptable personas is crucial for fostering natural, engaging, and trustworthy human-robot interaction (

researcharxiv-cs-ro

PACE: Provenance-Aware Capability Enforcement for Tool-Using LLM Agents

arXiv:2610.01349v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents turn generated text into real side effects, so poisoned tool metadata, retrieved pages, memory, and reusa

PACT: End-to-End Learning of Human Pose, Contacts, and Forces from Video

arXiv:2610.00451v1 Announce Type: cross Abstract: Human motion, environmental contacts, and interaction forces are governed by common physical laws, yet existing approaches typically separate visual p

PAGER: Partial-to-global Alignment via Geometric and Relational Distillation

arXiv:2610.01589v1 Announce Type: new Abstract: Pretrained 3D encoders are typically developed on globally reconstructed scenes expressed in a consistent world coordinate frame, whereas embodied syste

safetyarxiv-cs-cv

Parameter-Efficient Distributionally Robust Adaptation of Tabular Foundation Models under Subpopulation Shift

arXiv:2610.01143v1 Announce Type: cross Abstract: Despite strong mean accuracy, tabular foundation models (TFMs) can perform poorly on underrepresented groups under subpopulation shift, where group pr

Applications

Partial AUC Maximization from Positive-unlabeled Data

arXiv:2610.00284v1 Announce Type: cross Abstract: The partial area under the receiver operating characteristic curve (pAUC) is an important performance metric for binary classification that summarizes

applicationsarxiv-cs-ai

Participation-Sensitive Convergence and the Fragment First, Converge Later Pattern in Asynchronous Online Learning: A Topological Analysis Across 22 OULAD Courses

arXiv:2610.01738v1 Announce Type: cross Abstract: Asynchronous online learning offers temporal flexibility at a structural cost: learning communities tend to fragment rather than cohere. eta_0, the nu

safetyarxiv-cs-lg

Pay for the Fault, Not the Flow: Label-Free In-Flow Multi-Agent Workflow Optimization

arXiv:2610.01017v1 Announce Type: new Abstract: Large language models (LLMs) increasingly construct multi-agent workflows that decompose a complex task and assign specialist agents from a pool. Howeve

Paying for Too Many Tokens? Valid and Cost-Efficient Multimodal LLM Annotation with Simple Heuristics

arXiv:2610.00809v1 Announce Type: new Abstract: Vision-Language Models (VLMs) enable video annotation at scale, but costs accumulate quickly: processing a typical 60-second short-form video at one fra

pCoMole: Pareto-Constrained Molecule Editing with Discrete Flows

arXiv:2610.01663v1 Announce Type: new Abstract: Biomolecular therapeutics often start from known sequences and require targeted editing to improve multiple properties while satisfying hard biochemical

Peacebell - a from-scratch small language model

model-releasesr-localllama

I've been using my free time during weeknights and weekends for the last 11 months working on and refining a small domain-specific language model. It specializes on information about World War II. The

Per-Node Activation Function Evolution in Indirectly Encoded Substrates: Solvability, Limits, and Emergent Diversity

arXiv:2610.00149v1 Announce Type: cross Abstract: Biological neurons achieve computational diversity through specialized types: tonic, bursting, adapting, and fast-spiking cells coexist within the sam

Permutation-Robust Decision Modeling with Candidate-Independent Block-Causal Attention

arXiv:2610.01601v1 Announce Type: cross Abstract: Decision models often score a variable-sized set of candidate actions encoded in a single sequence. This setting is increasingly relevant for System 1

Persistent Depth Ordering amid Shifting Block-Bypass Responses in Language Model Pretraining

model-releasesarxiv-cs-lg

arXiv:2610.01165v1 Announce Type: new Abstract: Layer interventions are widely used to probe the internal organization of language models, yet most analyses examine a single training checkpoint even t

Personalized Image Generation with Reasoning and Reflection

arXiv:2610.00737v1 Announce Type: cross Abstract: Personalized image generation has remained narrowly focused on conditional synthesis from curated visual exemplars, rather than capturing who a user i

PG-SFT: Balancing Capability Acquisition and Retention in Offline Agent Fine-Tuning

arXiv:2610.00949v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) on offline agent trajectories is the standard approach for training specialized tool-using agents, but forcing models to im

PhaseAT: Fourier Phase Adversarial Training for Medical Image Domain Generalization

arXiv:2610.01807v1 Announce Type: new Abstract: Reliable clinical deployment of deep medical image models is hindered by distribution shifts across scanners, sites, and acquisition protocols. Existing

PhGPO: Pheromone-Guided Policy Optimization for Long-Horizon Tool Planning

arXiv:2602.13691v2 Announce Type: replace Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated strong capabilities in executing complex tasks through tool use. However,

safetyarxiv-cs-ai

Applications

PhysDEM: Physics-Defined Energy-Matching Diffusion for Spatiotemporal Field Generation under Scarce Measurements

arXiv:2610.01759v1 Announce Type: new Abstract: Generating and predicting spatiotemporal physical fields from scarce measurements is challenging, as observations are insufficient to characterize a dis

applicationsarxiv-cs-cv

Local Ai

Physics-Refined Spatiotemporal Forecasting on Open-Boundary Hydrologic Graphs

arXiv:2610.01765v1 Announce Type: new Abstract: Spatiotemporal forecasting on hydrologic graphs is especially prone to instability in open-boundary systems, where the forecast domain exchanges fluxes

local-aiarxiv-cs-lg

PhysicsLENS: Diagnosing Physical Property Blindness in Video Generation Models

arXiv:2610.01162v1 Announce Type: new Abstract: Reliable video world models could provide scalable predictive environments for robot learning, planning, and evaluation. However, generated robot videos

PhysVista: Benchmarking Physical Intelligence in VLMs via a Perception-Reasoning-Assessment Loop

arXiv:2610.00559v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong multimodal reasoning capabilities, yet whether they truly capture the physical consistency underlying re

Tutorials

PI-AMFM: Permutation-Invariant Learning for Variable-Cardinality AM-FM Mode Decomposition in Biomedical Signal Analysis

arXiv:2610.00819v1 Announce Type: cross Abstract: Physiological recordings often contain nonstationary oscillatory components whose number and dynamics vary across signals. Amplitude- and frequency-mo

tutorialsarxiv-cs-lg

PickMoment: Continuous-Time Single-Image-to-Video via Learning Deblurring and Blur-to-Video

arXiv:2610.01279v1 Announce Type: cross Abstract: Motion blur arises from the temporal integration of a continuous sharp signal over a finite exposure window, yet existing learning-based methods sides

PixelDense: Dense Prediction as Representation Alignment for Pixel Diffusion

arXiv:2610.00483v1 Announce Type: new Abstract: Representation alignment (REPA) accelerates diffusion transformer training, but its alignment targets are almost exclusively semantic encoders such as D

safetyarxiv-cs-cv

Platonic Task Arithmetic

arXiv:2610.00929v1 Announce Type: cross Abstract: Models specialized for the same task converge to similar behavior, yet the parameter updates that produce it share no common coordinate system, so wei

Please check out @DeepSeekHarness. We just released packaged desktop versions for macOS and Windows; Linux users can get it from the @deeps…

model-releasesdeepseek--x

Please check out @DeepSeekHarness. We just released packaged desktop versions for macOS and Windows; Linux users can get it from the @deepseek-ai/dsh package on npm. https://deepseek.com/harness Deep

Poincare Meets Bellman: Revisable Memory, Operational Quotients, and Evidence-Supported Learning in Changing Environments

model-releasesarxiv-cs-lg

arXiv:2512.05990v2 Announce Type: replace Abstract: Memory consolidation determines both what a learner can do now and which changes remain implementable later. We develop a finite-model synthesis of

Polylogarithmic Sparsity of Randomly Reweighted NPMLEs for Gaussian Mixtures

arXiv:2610.01088v1 Announce Type: cross Abstract: The nonparametric maximum likelihood estimator (NPMLE) of a Gaussian location mixture maximizes the likelihood over the infinite-dimensional space of

Pooling Helps, Learned Weighting Hurts In-Context: Decomposing Group Attention

arXiv:2610.01831v1 Announce Type: new Abstract: Group attention, introduced by the time series forecasting model Chronos-2, attends over the variates of a group at a fixed patch index and serves both

Port-Hamiltonian Neural Networks for Systems with Multiple Asymptotically Stable Equilibria

arXiv:2610.01356v1 Announce Type: new Abstract: Stable port-Hamiltonian neural networks certify asymptotic stability by construction. Yet, their Hamiltonian is a global Lyapunov function with a single