All entries

GPT-6 Sol and Luna are great models but also these characters are so cute Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe. GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, br

industrysam-altman--x

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Applications

GPT-6 Sol and Luna roll out today in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise, and Edu users. Both are also available in t…

DGX agent

GPT-6 Sol and Luna roll out today in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise, and Edu users. Both are also available in the API. Free and Go users can try GPT-6 Luna in the desktop

applicationsopenai--x

22 Sept 2026

GPT-6 Sol costs 2/1M input and 10/1M output tokens, and GPT-6 Luna costs 0.10/1M input and 0.50/1M output tokens, both about 50% cheaper than GPT-5.6 (Nat Rubio-Licht/The Deep View)

Nat Rubio-Licht / The Deep View: GPT-6 Sol costs 2/1M input and 10/1M output tokens, and GPT-6 Luna costs 0.10/1M input and 0.50/1M output tokens, both about 50% cheaper than GPT-5.6 — OpenAI is relea

model-releasestechmeme

GPT‑6 Sol and Luna build on Astra’s advances in alignment, showing improvements over their GPT-5.6 counterparts.

OpenAI announced the GPT‑6 Sol and Luna models on September 22 2026. These variants incorporate advances from the Astra project, yielding improved alignment safety relative to earlier GPT‑5.6 systems.

model-releasesopenai--x

GRACE: Grounded Adversarial Reasoning over Canadian Law

arXiv:2609.23726v1 Announce Type: new Abstract: Large language models have shown strong performance across a range of legal tasks, but existing benchmarks rarely evaluate the ability to take and defen

safetyarxiv-cs-cl

Graded-Relevance Composed Multimodal Retrieval for E-commerce Visual Search at Scale

arXiv:2609.24152v1 Announce Type: cross Abstract: Visual search on large e-commerce catalogs must serve both 'similarity' queries that ask for items resembling an uploaded image and 'modifier' queries

Hardware

Gradient-estimator design overcomes trainability barriers in neural-network-based variational optimization

arXiv:2609.22342v1 Announce Type: cross Abstract: Neural networks provide expressive representations for scientific computing. However, even sufficiently expressive networks can suffer training failur

hardwarearxiv-cs-lg

GrapeSplat: Geometry-Grounded Reconstruction via Amalgamated Pose-Free Encoding for Feed-Forward 3D Gaussian Splatting

arXiv:2609.23182v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting now reconstructs renderable scenes from unposed, uncalibrated images. Yet, most models supervise only photometric con

Graph Learning for Cross-Subject, Cross-Population EEG Emotion Decoding and Model-Derived Spatial-Spectral Neural Signatures

arXiv:2609.22103v1 Announce Type: cross Abstract: Electroencephalography (EEG) provides a noninvasive means of capturing emotion-related neural dynamics, yet reliable EEG emotion decoding lacks models

Graph-to-Grid (G2G): Continuous-Coordinate Feature Painting for Soccer Pass Surfaces

arXiv:2609.24040v1 Announce Type: cross Abstract: Dense pass surfaces give, for every pitch cell, whether a pass played there would arrive, whether the carrier would choose it, and what the possession

GraphSVR: q-Space--Aware Graph-Based Slice-to-Volume Registration for Diffusion MRI

arXiv:2609.24732v1 Announce Type: new Abstract: Diffusion-weighted imaging (DWI) remains highly vulnerable to subject motion, particularly in time-efficient protocols and in motion-prone populations.

GraphToolbox: A Configurable Python Framework for Graph Neural Network Forecasting

arXiv:2609.24609v1 Announce Type: new Abstract: Electricity forecasting often involves spatially related signals observed over regions, substations, and feeders, and Graph Neural Networks (GNNs) provi

GraspTune: Tactile-Driven Execution Refinement for Robust Grasping

arXiv:2609.24180v1 Announce Type: new Abstract: Visual grasp proposal generation has advanced rapidly, yet converting a selected proposal into a stable physical grasp remains a central execution-stage

safetyarxiv-cs-ro

Great paper from Google and colleagues. Trains Text-to-SQL agents using multi-agent RL. (bookmark it) This work proposes DualSQL, which spli…

Great paper from Google and colleagues. Trains Text-to-SQL agents using multi-agent RL. (bookmark it) This work proposes DualSQL, which splits Text-to-SQL into two agents, one that links the question

agentsdair-ai--x

Great prompt from Anthropic. It helps steer long runs when using Opus 5.5 in Claude Code. Apparently, on long-running tasks, the model somet…

Great prompt from Anthropic. It helps steer long runs when using Opus 5.5 in Claude Code. Apparently, on long-running tasks, the model sometimes stops to report instead of continuing. I've noticed tha

model-releasesdair-ai--x

Ground-Truth Subgraphs for Better Training and Evaluation of Knowledge Graph Augmented LLMs

model-releasesarxiv-cs-cl

arXiv:2511.04473v3 Announce Type: replace-cross Abstract: Retrieval of information from graph-structured knowledge bases represents a promising direction for improving the factuality of LLMs. While va

Grounded Action Model: 3D Grounding as a Foundation for Robotics

arXiv:2609.23863v1 Announce Type: new Abstract: Manipulation policies must know which objects matter and where they are, yet the pretrained backbones that current robot foundation models build on, fro

safetyarxiv-cs-ro

GRRR: The Geometry of Reshaping, Rotation, and Routing in Decoder LLM post-training

arXiv:2609.22146v1 Announce Type: cross Abstract: We study how post-training changes the weights of Large Language Models (LLMs) relative to their pretrained weights. Across 12 post-training chains wi

researcharxiv-cs-cl

Guaranteed Low-Rank Tensor Recovery from Modewise Measurements via Normalized Block-Weighted Riemannian Gradient Descent

arXiv:2609.24679v1 Announce Type: new Abstract: We consider the recovery of low-multilinear-rank tensors from linear measurements and propose an adaptive block-weighted modewise Riemannian gradient de

Guiding the coarse levels of semantic IDs makes the fine levels learnable

arXiv:2609.22227v1 Announce Type: cross Abstract: Generative retrieval represents each item by a short Semantic ID and casts recommendation as autoregressive generation of that sequence. Because the t

safetyarxiv-cs-cl

H-Spec: Parallel Speculative Decoding Without a Drafter-Side KV Cache

arXiv:2609.24197v1 Announce Type: new Abstract: Speculative decoding losslessly accelerates large language model inference by having a lightweight draft model predict future tokens for verification by

H-VLA: Hierarchical Vision-Language-Action Model with Key-Action Reasoning and Motion Planning in a Unified Action Space

arXiv:2609.22895v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but many existing methods still rely on direct mappings from l

researcharxiv-cs-ro

H2LooP Telecom Model v1: From Telecom Comprehension to Autonomous Issue and PR Resolution

model-releasesarxiv-cs-cl

arXiv:2609.22241v1 Announce Type: new Abstract: We present H2LooP Telecom Model v1, a domain-specialized large language models fine-tuned for the telecommunications industry. We release two domain-ada

H2RBench: A Real-to-Sim Benchmark for Evaluating Human-to-Robot Transfer

model-releasesarxiv-cs-ro

arXiv:2609.24778v1 Announce Type: new Abstract: Learning robot manipulation policies from human video demonstrations constitutes a promising avenue for scalable robot learning. However, comparing diff

HaikuS2S: A Cascaded System For Responding In Verse

arXiv:2609.23951v1 Announce Type: new Abstract: Expressive speech synthesis has advanced through prosody modeling, yet generating structured poetic speech, such as haiku, remains challenging. Prior wo

safetyarxiv-cs-cl

HappyWorld-Bench

arXiv:2609.24308v1 Announce Type: new Abstract: Evaluating world models requires assessing both the quality of the worlds they generate and their consistency and responsiveness under exploration, inte

HapticWAM: Distilling Imagined Touch into a World-Action Model without Inference-Time Tactile Sensing

arXiv:2609.23888v1 Announce Type: new Abstract: Contact-rich manipulation requires estimating forces, slip and contact geometry that can remain ambiguous in scene images. Optical tactile sensors provi

safetyarxiv-cs-ro

Harness-Zero: Harness Distillation via Agent-as-Harness

arXiv:2609.24974v1 Announce Type: cross Abstract: Agent harnesses, the external systems that mediate model-environment interaction, can substantially improve agent performance, but their gains remain

agentsarxiv-cs-cl

Local Ai

HDMamba-YOLO: Efficient State-Space Perception and Local Spatial Reconstruction for UAV Small Object

arXiv:2609.23061v1 Announce Type: new Abstract: Small-object detection in UAV imagery is challenged by weak visual evidence, ambiguous boundaries, dense object distributions, and complex backgrounds.

local-aiarxiv-cs-cv

HDND: Hierarchical Dynamic Neural Decoding for Multilingual Word/Character Retrieval from Non-Invasive Brain Recordings

arXiv:2609.24095v1 Announce Type: new Abstract: While deep learning has enabled language decoding from intracranial brain recordings, extending this capability to non-invasive recordings remains an un

HEARTH: An Object-Centric RGB-Thermal-3D Dataset for Temperature-Aware Robot Manipulation

arXiv:2609.23418v1 Announce Type: new Abstract: Language-guided manipulation can depend on physical properties that visible appearance does not reveal. Temperature is one such property, but object dat

researcharxiv-cs-ro

Applications

Heidi Health nabs $340M to deepen adoption of AI agents within health systems globally

Heidi Health Trading Pty Ltd., a healthcare artificial intelligence startup, today announced it has raised a total of 340 million in new funding to support the company’s next phase of growth and deepe

applicationssiliconangle

Helix-FNO: Spectral-Domain Operator Learning Coupled with a High-Fidelity Mechanistic Model for Fast Surrogate Simulation

arXiv:2609.22129v1 Announce Type: new Abstract: Mechanistic simulation models of full-scale treatment processes remain the only trustworthy, extrapolative description of the underlying physico-chemica

Hello, new to CLI and Opensource AI but running into a issue with gemma4:26b

I keep trying to get it to write code and test simpel stuff but it never finsihes conversation its always stopping mid way. i installed it through qwen > ollama. currently removed it and trying to rei

model-releasesr-ollama

Applications

Hessian Rank Constraint for Learning Structure of Nonlinear Latent Variable Models

arXiv:2609.24241v1 Announce Type: new Abstract: Uncovering latent variables and their causal relations from observed data is a fundamental yet challenging problem. Existing methods often rely on restr

applicationsarxiv-cs-lg

Applications

Heterogeneous Robot Collaboration in Unstructured Environments with Grounded Generative Intelligence

arXiv:2510.26915v2 Announce Type: replace Abstract: While heterogeneous teams have typically been designed for well-specified missions with known semantics, generative intelligence, i.e., large langua

applicationsarxiv-cs-ro

HFEMCNet: A Compact Hybrid Frequency Enriched Multi Channel Network for Automatic Modulation Classification

model-releasesarxiv-cs-lg

arXiv:2609.22139v1 Announce Type: cross Abstract: Automatic modulation classification (AMC) of received radio signals is prudent for further signal processing tasks such as communication monitoring, c

Hi Ollama People!

Hi everyone, I wanted to ask you a question. I’m developing an app, and I’m currently putting together a list of the best AI models, especially, but not necessarily, in GGUF format and using Q4_K_M qu

model-releasesr-ollama

Hi-Singers: A Comprehensive High-Quality Dataset for Expressive Audio-Driven Singing Head Synthesis

arXiv:2609.22264v1 Announce Type: cross Abstract: State-of-the-art models for audio-driven digital human generation have achieved photo-realistic results in talking-head synthesis. However, extending

HiBerNAC: Hierarchical Brain-inspired Robotic Neural Agent Collective for Disentangling Complex Manipulation

arXiv:2506.08296v3 Announce Type: replace Abstract: Recent advances in multimodal vision-language-action (VLA) models have revolutionized traditional robot learning, enabling systems to interpret visi

agentsarxiv-cs-ro

Hierarchical Aggregation of Semantic Uncertainty in 3D Scene Graphs

arXiv:2609.22351v1 Announce Type: new Abstract: Open-vocabulary 3D Scene Graphs (3DSGs) ground each object node in a vision-language embedding, yet they record every entry as equally certain, so a rob

Hierarchical Bayesian optimization of an aircraft-based multi-agent system-of-systems

arXiv:2609.22130v1 Announce Type: new Abstract: Developing innovative system architectures increasingly relies on advanced modeling and optimization techniques to frame the architecting process and de

agentsarxiv-cs-lg

Hierarchical Prompt Learning for Hyperbolic Vision-Language Models

arXiv:2609.24276v1 Announce Type: new Abstract: Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstre

HIGenNTO: Scalable Humanoid Interaction Generation via Noise-Space Trajectory Optimization

arXiv:2609.22611v1 Announce Type: new Abstract: Humanoid robots can acquire complex skills by imitating kinematic humanoid motion references, yet reliable references for contact-rich interactions rema

agentsarxiv-cs-ro

High-Dimensional Online Change Point Detection with Adaptive Thresholding and Interpretability

arXiv:2609.24278v1 Announce Type: new Abstract: Change point detection (CPD) identifies abrupt and significant changes in sequential data, with applications in human activity recognition, financial ma

agentsarxiv-cs-lg

High-resolution Nitrogen Dioxide Maps Reveal Exposure Limit Breaches across Europe

arXiv:2609.24634v1 Announce Type: new Abstract: Nitrogen dioxide (NO2) is a common air pollutant, released into the atmosphere through the incomplete burning of fossil fuels, and associated with respi

Higher usage limits and lower cost give you more flexibility and room to iterate.

In a tweet posted on September 22, 2026, OpenAI noted that increasing usage limits while lowering costs gives users greater flexibility and more room to iterate on their projects. This announcement hi

model-releasesopenai--x

Highly-Efficient Differentiable Simulation for Robotics

model-releasesarxiv-cs-ro

arXiv:2409.07107v3 Announce Type: replace Abstract: Robotics simulators have improved significantly in computational speed and scalability, enabling them to generate years of simulated data for comple