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Omni2LoRA: Coherence-Preserving Parametric Memory for Efficient Omni Language Models

arXiv:2608.09227v1 Announce Type: new Abstract: Omnimodal language models (OLMs) enable unified audio-visual understanding, but processing long joint token sequences makes inference computationally pr

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OmnilingualGAIA2: Evaluating the Multilingual Gap in Frontier AI Agents

DGX agent

arXiv:2608.08775v1 Announce Type: new Abstract: Agentic benchmarks aim to measure how well AI agents plan, search, execute, and recover within realistic multi-tool environments, but they are almost ex

model-releasesarxiv-cs-cl

11 Aug 2026

Local Ai

On-Device Multi-Species Malaria Detection with Uncertainty-Calibrated Slide-Level Aggregation

arXiv:2608.08566v1 Announce Type: cross Abstract: Malaria remains a leading cause of mortality in resource-limited settings, where expert microscopists are scarce. Automated diagnosis based on microsc

local-aiarxiv-cs-ai

On the Effect of Sampling Diversity in Scaling LLM Inference

arXiv:2502.11027v5 Announce Type: replace Abstract: Large language model (LLM) scaling inference is key to unlocking greater performance, and leveraging diversity has proven an effective way to enhanc

On the expressivity of deep Heaviside networks

arXiv:2505.00110v2 Announce Type: replace-cross Abstract: We show that deep Heaviside networks (DHNs) have limited expressiveness but that this can be overcome by including either skip connections or

On the Robustness of LLMs' Internal Representation of Code Correctness

arXiv:2608.08266v1 Announce Type: cross Abstract: Code generated by modern language models often reads naturally. Yet, it also often fails to implement what was asked. This should be no surprise, as r

On the use of foundation models in cognitive science

arXiv:2608.07812v1 Announce Type: new Abstract: A host of recent studies have evaluated the cognitive and developmental alignment of Foundation Models (FMs). These investigations include evaluations o

safetyarxiv-cs-cl

One Adapter Pair per Model: A Universal Activation Interface for Language Models

arXiv:2608.09521v1 Announce Type: new Abstract: Activation-based tools are usually tied to one model's native hidden space, requiring probes, sparse autoencoders, and natural-language interpreters to

One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training

arXiv:2608.09403v1 Announce Type: new Abstract: Whole slide images (WSIs) in digital histopathology are acquired at discrete magnification levels encoding complementary diagnostic information from glo

Local Ai

One-Time Training for All Grains: Open-Set Grain Recognition and Quantitative Analysis

arXiv:2608.09345v1 Announce Type: new Abstract: Advances in crop breeding have introduced an increasing number of grain varieties, creating a growing demand for efficient variety recognition and quant

local-aiarxiv-cs-cv

OnEvoMemory: Evolving Memory through Online Robot Rollouts for Pretrained Robot Policies

arXiv:2608.08749v1 Announce Type: new Abstract: Long-horizon robot manipulation requires policies to track completed subtasks and critical interaction events. However, existing memory mechanisms heavi

safetyarxiv-cs-ro

Online Learning of Scale Parameters in Score-Driven Filters

arXiv:2608.09218v1 Announce Type: new Abstract: Score-driven filters multiply a scaled log-likelihood score by a gain that controls the update magnitude. We treat this gain as a decision variable and

Open Evaluation Agent: Efficient and Promptable Evaluation of Visual Generative Models

arXiv:2608.09666v1 Announce Type: new Abstract: Recent advances in visual generative models have enabled high-quality image and video generation, but evaluating these models often demands sampling hun

Open source is so back. Zuck just announced Meta is opening the weights for Muse Glimmer, with Muse Spark 1.2 coming soon But a year ago, ev…

model-releasesrowan-cheung--x

Open source is so back. Zuck just announced Meta is opening the weights for Muse Glimmer, with Muse Spark 1.2 coming soon But a year ago, everyone doubted Meta's position in the AI race In an intervie

Open-World Hierarchical Perception: Taxonomic Abstraction over Class-Agnostic Proposals for the Safe Handling of Out-of-Vocabulary Road Objects

arXiv:2608.07577v1 Announce Type: cross Abstract: A closed-set detector for autonomous driving must assign every object one of a fixed set of labels. On an object outside that set (a horse-drawn carri

Open-World Semantic Segmentation with Sensitivity Modeling

arXiv:2608.08308v1 Announce Type: cross Abstract: Modern vision systems must operate in 'open-world' settings, where models must recognize known categories and detect unseen or anomalous content. Conv

Industry

OpenAI is hiring a power-trading lead to manage commodity hedging across its expanding data center power portfolio, as tech companies seek reliable electricity (Julian Hast/Bloomberg)

Julian Hast / Bloomberg: OpenAI is hiring a power-trading lead to manage commodity hedging across its expanding data center power portfolio, as tech companies seek reliable electricity — OpenAI is hir

industrytechmeme

OpenAI just launched a cybersecurity model that answers 95% of advanced threat queries. And Meta put a frontier model on your laptop. Same day.

Something happened today that I think most people are going to miss because there are two separate stories and neither one is getting the full picture. OpenAI expanded Daybreak. If you haven't heard o

model-releasesr-chatgpt

OpenAI launches a ChatGPT desktop app for Linux in preview, supporting ChatGPT Work, Codex, and more; Computer Use outside the in-app browser is not available (Frederic Lardinois/The New Stack)

Frederic Lardinois / The New Stack: OpenAI launches a ChatGPT desktop app for Linux in preview, supporting ChatGPT Work, Codex, and more; Computer Use outside the in-app browser is not available — On

model-releasestechmeme

OpenLoopEvolve: A Verifiable Self-Evolution Framework for Loop Policies in Long-Horizon Complex Tasks

arXiv:2608.09380v1 Announce Type: new Abstract: Long-horizon complex tasks require agents to repeatedly observe states, formulate plans, invoke tools, verify results, and recover from failures in cont

OpenMHC: Accelerating the Science of Wearable Foundation Models

arXiv:2607.16235v3 Announce Type: replace-cross Abstract: Mobile and wearable devices offer an unprecedented opportunity for continuous, passive health monitoring and active health coaching. However,

OpenVisTool: An Open Recipe for Synthesizing Instructive Visual Tool-Use Trajectories

model-releasesarxiv-cs-cl

arXiv:2608.08557v1 Announce Type: new Abstract: Visual tool use has emerged as a fundamental capability for multimodal agents to actively acquire evidence beyond a fixed image encoding. The prevailing

OpenWALDO launches to build collaborative community for open-source AI

model-releasessiliconangle

OpenWALDO, a new open-source artificial intelligence project sponsored by Ctrl IQ Inc., launched today, led by Gregory Kutzer, the founder of Rocky Linux, CentOS and Apptainer. The project aims to bui

Opportunity Is Not Realizability: Selection-Valid Diagnostics for Multi-LLM Routing

arXiv:2608.08265v1 Announce Type: new Abstract: Oracle routing measures how much a pool of language models could gain from per-query selection, but the diagnostic has two flaws: testing against a best

Optimal Learning Under Tsybakov Noise

arXiv:2608.08416v1 Announce Type: new Abstract: Probably Approximately Correct (PAC) learning [Val84] is a fundamental learning model that has been extensively investigated. In this model, H subseteq

Optimal Multi-Agent Path Finding in Continuous Time

model-releasesarxiv-cs-ro

arXiv:2508.16410v3 Announce Type: replace-cross Abstract: Continuous-time Conflict Based Search (CCBS) has been widely used as an exact baseline for Continuous-time Multi-Agent Path Finding (MAPFR), a

Optimal Transport for Machine Learners

arXiv:2505.06589v3 Announce Type: replace-cross Abstract: Modern machine learning repeatedly manipulates probability measures: empirical datasets, generated samples, latent distributions, class-condit

Other active promotions: - Free models: Solar Pro 4 (1 week), Hy3, Step 3.7 Flash, Laguna S and XS - 90% off DeepSeek V4 Flash for ~2 more d…

model-releasesnous-research--x

Nous Research has extended its 20 % discount on all models—including high‑end frontier options—throughout the Nous Portal for an additional two weeks (until the end of April). Free model trials such a

Ouroboros: A Self-Developing Frontier Coding Agent with Reviewed Core Evolution

arXiv:2608.08311v1 Announce Type: cross Abstract: We present Ouroboros, a self-developing agent harness whose tools, prompts, context assembly, and core implementation improve through reviewed commits

Out-of-Distribution Federated Distillation with Domain-Aware Proxy

model-releasesarxiv-cs-lg

arXiv:2608.08525v1 Announce Type: new Abstract: Federated Learning is a distributed machine learning paradigm that trains a global model by aggregating local clients without sharing private data of ea

Overcoming Data Scarcity and Confidentiality in Hardware Assurance via Synthetic Generation

arXiv:2608.09914v1 Announce Type: cross Abstract: Hardware assurance relies on scanning electron microscopy (SEM) to verify nanoscale structures, but assembling the large, high-quality datasets requir

OWN YOUR INTELLIGENCE Last year, building on open-weight models was primarily a cost rationalization exercise. Slightly worse performance fo…

OWN YOUR INTELLIGENCE Last year, building on open-weight models was primarily a cost rationalization exercise. Slightly worse performance for a much cheaper price. Now, it is increasingly an existenti

safetysonya-huang--x

Local Ai

P2Voxel: Pyramid Pivot Voxelization for 3D Mesh Tokenization

arXiv:2608.07549v1 Announce Type: cross Abstract: Triangle meshes provide explicit and accurate surface geometry, yet their irregular topology connectivity makes 3D mesh tokenization a geometric sampl

local-aiarxiv-cs-ai

P^{3}: Joint Program-and-Proof Planning for Verified Code Generation

arXiv:2608.09277v1 Announce Type: new Abstract: Verified code generation asks a large language model (LLM) to generate both an executable program and a machine-checkable proof that the program meets a

PACE: A Playback-Aligned Context Engine for LLM-Based Full-Duplex Voice Dialogue

arXiv:2608.07631v1 Announce Type: cross Abstract: LLM-based full-duplex voice services allow users to speak while the assistant is responding. Because servers can generate output and advance dialogue

PAM: Training Policy-Aligned Moderation Filters at Scale

arXiv:2505.19766v4 Announce Type: replace Abstract: Large language models (LLMs) remain vulnerable to misalignment and jailbreaks, making external safeguards like moderation filters essential, yet exi

safetyarxiv-cs-cl

PARAGraph: Pathology-Anatomy-Aware Hierarchical Graph for Diabetic Retinopathy Grading

arXiv:2608.08368v1 Announce Type: new Abstract: Diabetic retinopathy (DR) remains a leading cause of vision loss among working-age adults worldwide, making reliable severity grading clinically importa

Parameter-Dependent LMI Synthesis for Semi-Global Differential ISS Trajectory Tracking of Nonholonomic Mobile Robots Under Multiplicative Wheel Slip

model-releasesarxiv-cs-ro

arXiv:2608.08049v1 Announce Type: cross Abstract: This paper presents a parameter-dependent linear matrix inequality (LMI) framework for trajectory tracking of nonholonomic mobile robots subject to se

Parameter Exploration for RLVR via Variational Learning

arXiv:2608.09805v1 Announce Type: cross Abstract: Exploration has been a focus of reinforcement learning research for a long time. Recently, there has been growing evidence that it is also an importan

Parcel2Progression: An Anatomy-aware Longitudinal Framework for Alzheimer's Disease Diagnosis

arXiv:2608.08753v1 Announce Type: new Abstract: Alzheimer's disease (AD) progression is a longitudinal process with subtle pathological cues in the early stages. Yet, computational constraints have li

Agents

Particle-Based Conformal Prediction for Contact-Aware Uncertainty Calibration in Stratified Configuration Spaces

arXiv:2608.09166v1 Announce Type: cross Abstract: Reliable uncertainty representation is essential for deploying autonomous systems that interact with their environment, as robots must reason about ho

agentsarxiv-cs-lg

PAST: Privileged Adaptation from Complete Student Trajectories for On-Policy Self-Distillation

arXiv:2608.08726v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD) uses a privileged teacher to supervise a reasoning model on prefixes sampled from its own rollouts. Yet each rollou

safetyarxiv-cs-ai

PatchHead: Learning Spatial Patch Evidence for Generalizable AI-Generated Image Detection

arXiv:2608.09223v1 Announce Type: new Abstract: AI-generated image detectors generalize poorly when their training and test images originate from different generators or datasets. Despite the rich spa

Path-dependent Discrete Amortized Inference

model-releasesarxiv-cs-lg

arXiv:2608.08644v1 Announce Type: new Abstract: We consider the problem of sampling compositional and discrete objects from a given unnormalized posterior distribution. Notably, recent studies have sh

PATH: Next-Interval Prediction via Autoregressive Tree Hierarchy on Tabular Data

arXiv:2608.08078v1 Announce Type: new Abstract: Interval prediction aims to achieve a target coverage level while producing intervals that are as short as possible. Many conformal regression pipelines

PE-Mamba: Bidirectional Selective Layer Aggregation for AI-Generated Image Detection

arXiv:2608.07999v1 Announce Type: new Abstract: AI-generated image (AIGI) detection has become increasingly challenging due to the rapid advancement of generative models and the diminishing gap betwee

PEEL: Parallel Extraction for Long-Horizon Disassembly Planning via Scale-Invariant Sampling

arXiv:2608.08773v1 Announce Type: new Abstract: Long-horizon multi-part object disassembly requires robots to compute feasible sequences of collision-free removal motions, even in the presence of tigh

researcharxiv-cs-ro

Penalizing Length: Uncovering Systematic Bias in Quality Estimation Metrics

arXiv:2510.22028v4 Announce Type: replace Abstract: Quality Estimation (QE) metrics are vital in machine translation for reference-free evaluation and increasingly serve as selection criteria in data

safetyarxiv-cs-cl