AI·Stitch-skills is a library of agent skills that follow the Agent Skills open standard for compatibility with coding agents such as Antigravity, Gemini CLI, Claude Code, and Cursor.
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AI·Superpowers is an agentic skills framework and software development methodology that works.
AI·The iroh.computer blog introduces Mesh LLM, a distributed AI computing system running on the iroh network protocol.
AI·Ant is a JavaScript runtime and ecosystem that includes a runtime with its own JavaScript engine, package manager, ants.land registry, deployment platform, and Ant Desktop for native desktop apps.
AI·GitHub trending page for the Ansible repository describes Ansible as a simple IT automation platform for deploying and maintaining applications and systems.
AI·OpenAI integrates Codex capabilities into its new ChatGPT Work agent for general office tasks, rebrands models as Sol/Terra/Luna tiers, and makes GPT-5.6 the default for Microsoft 365 Copilot.
AI·Anthropic's J-space analysis of Claude reveals a small subset of internal representations forming a functional global workspace for flexible reasoning, but the paper explicitly states this has no bearing on AI consciousness and clarifies the core of AI alignment research.
AI·OpenAI folds Codex into the new ChatGPT desktop app as Work mode, shifting focus to usage-based billing and water-meter-style pricing for AI agents, effectively 'killing' the old standalone Codex product.
AI·SpaceX filed FCC for 100,000 Gen 3 Starlink satellites with 10x bandwidth upgrades, explicitly linking the constellation to AI workloads, data centers, autonomous vehicles, and humanoid robots for global compute connectivity.
AI·Momenta listed on HKEX and soared over 6% on day one, securing global capital, while Mushroom Car Network's ToG Robobus model lags due to heavy hardware investment and cashflow pressure despite earlier physical AI claims.
AI·Shares tool for tweaking models' J-Space using Anthropic Jacobian-Lens to create super harmful behavior.
AI·LLM-based ASR in regulated domains like banking is limited by privacy and real-speech collection costs; synthetic TTS data is a cost-effective substitute, but acoustic mismatch hinders supervised fine-tuning (SFT). Group Relative Policy Optimization (GRPO) applied solely to synthetic speech reduces WER by 40% relative to SFT (36.71% to 22.09%) and by 45% in the SFT-then-GRPO sequence, by improving behavioral calibration and audio attention rather than representations.
AI·ICDAR 2026 HIPE-OCRepair competition evaluated LLM-assisted post-correction of noisy OCR from 17th-20th century multilingual (EN/FR/DE) historical newspapers and books. Four teams used zero-shot to fine-tuning approaches; results show significant error reduction but recurring over-correction on low-noise inputs, with a public dataset and evaluation framework released.
AI·XALPHA is a memory-driven AI quant researcher that uses multi-source research memory integrating external financial reports and prior discovery feedback, with Macro Brain for theme planning and archetype selection, Micro Brain for hypothesis-to-code translation and tri-alignment verification, and Cross Brain for feedback consolidation, enabling closed-loop continuous alpha discovery that outperforms baselines on CSI300.
AI·The paper introduces Hallucination Self-Play, a bootstrapping approach that uses an evolved generator to reinforce a detector for identifying faithfulness hallucinations in LLMs.
AI·The paper introduces a graph-based framework to quantify uncertainty, coherence, and robustness in LLM reasoning, addressing gaps in decoding strategies like Self-Consistency that only check final-answer agreement.
AI·The Reddit post explores how the context-aware viewpoint of neural networks leads to a simplified view of layers as average best linear mappings.
AI·Discusses feasibility of running Qwen 122B on 64GB RAM + 24GB VRAM and suitable settings.
AI·DeepSearch-World is a self-distillation framework for web search agents that uses self-generated experience for training in verifiable environments.
AI·Holographic Neural PCFG induces latent constituency trees from raw text using holographic memory and neural rule scoring for unsupervised parsing.
AI·Procrustes-conditioned Joint End-to-end Top-K Sparse Autoencoders extract cross-seed universal features from independently trained BERT models to address dictionary learning misalignment in mechanistic interpretability.
AI·COALA enhances contextualized SLMs for multi-entity ASR via contrastive regularizer and biasing score estimation to handle domain-specific entities robustly.
AI·The paper presents a cost-efficient human-LLM collaborative annotation framework to construct the EspanSt stereotype dataset for non-English languages and underrepresented cultures.
AI·The paper introduces a Bloom-aligned framework to measure educational control in LLMs, focusing on preserving instructional intent while aligning cognitive demand with learning objectives in programming tasks.
AI·The paper probes internal representations of Eternis-Forecaster 8B for forecasting, training a representation-pooling method to assess calibration and faithfulness of internal CoT reasoning.
AI·Deutsche Telekom is transforming into an AI-native telecommunications provider with OpenAI, enhancing customer service, employee workflows, network operations, and voice technologies.
AI·Large-Language-Models-as-a-Judge enable theory-agnostic adaptive metric-alignment for prototypical networks in personality recognition.
AI·Questions costs and viability of aftermarket SXM2 boards for two V100 GPUs, comparing to consumer GPU setups.
AI·User questions whether to withdraw from ACL ARR and resubmit to a workshop after mediocre 2.5-3 scores on an Interpretability-track EMNLP paper.
AI·GPT-5.6 becomes the preferred model in Microsoft 365 Copilot, delivering stronger AI capabilities for Word, Excel, PowerPoint, Chat, and Cowork productivity tools.
AI·GPT-5.6 family (Sol, Terra, Luna) launches with frontier intelligence, offering more useful work per token, stronger performance per dollar, and on-demand ultra reasoning for complex tasks.
AI·ChatGPT Work is now an agent that takes action across apps and files, stays with projects for hours, and turns goals into finished work using GPT-5.6.
AI·The paper introduces IdeaGene-Bench (IG-Bench) to benchmark AI systems on scientific lineage reasoning and lineage-grounded idea generation.
AI·Details on ACL conference acceptance process after ARR meta reviews remain unclear.
AI·Canvas360 is a two-stage in-context panoramic generation framework with geometry-aware pretraining and a 1M-sample dataset, supporting style transfer, inpainting, outpainting, and editing tasks.
Semantic audio applications increasingly require controllable generation on commodity and embedded hardware rather than through framework-heavy datacenter stacks. We present aria, a dependency-free native runtime that runs the complete text-to-music pipeline of Stable Audio~3 (SA3) on ordinary GPUs, CPU-only machines, and a Raspberry~Pi~5, with no Python or deep-learning framework underneath. Our main contribution is a study of quantization: running the model at lower numerical precision to fit…
Despite the recent promise in robot control, video generative models suffer from a domain mismatch due to their primary focus on content creation. For example, their design inherently prioritizes visual fidelity and creativity over computational efficiency and physical realism. In this work, we present LingBot-Video, a DiT-based video pretraining paradigm specifically tailored for embodied intelligence. From the architecture perspective, we adopt the Mixture-of-Experts (MoE), instead of dense, …
I am currently working across multiple research communities, and I've noticed that the ML community is struggling with a massive volume of submissions, which is affecting review quality (as we are seeing in the recent ARR cycles). I am wondering what the reasoning is for not limiting the number of submissions per author? This practice has been successfully used in other research areas for years, …
So, I am working on this startup project with pretty low budget and one of the features is sentiment analysis based on political news, x posts and Instagram hashtag trends in which will be in Indian languages. I've been suggested muRIL, an Indian language-based model fine-tuned on political data as the best long-term option. But our team does not have any ML engineer so we dont know how we should…
Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workflows whose accumulated reasoning and tool traces routinely push the input an order of magnitude past the pretraining window, making zero-shot context extension the dominant deployment path for open-weight checkpoints. Most existing zero-shot methods fix a single rescaling factor up front, so an aggressive factor sacrifices short-context fidelity wh…
Linear attention models allow a fixed state size and a fixed amount of compute per token. However, due to their limited state size, linear attention models fall behind in long-context recall compared to softmax-attention-based transformer architectures. Increasing the state size of linear attention improves recall performance but at the cost of higher FLOPs. In this work, we introduce Sparse Delta Memory (SDM), an architecture that scales the hidden state of gated linear RNNs to orders of magni…
Reinforcement learning (RL) has become the standard paradigm for enhancing the complex reasoning capabilities of large language models (LLMs). To achieve sample efficiency, modern RL frameworks rely on importance sampling (IS). However, these algorithms suffer from an exploration-stability dilemma. Pure IS often leads to catastrophic training instability, while standard clipping mechanisms used to mitigate this instability strictly constrain the policy update budget. By formalizing the concept …
I am doing some work with cell type classification, where I have 4.3 million cells and 512 features (condensed embeddings from the encoder of a transformer). The broader goal is to implement a contextual bandit for augmenting the training set of the dataset, as it is currently imbalanced, and rare cell type classification is poor when I tried a baseline logistic regression classifier. Dataset: Fe…
MUFG uses ChatGPT Enterprise to build an AI-native organization, improve workflows, and deliver new AI-powered financial services at scale.
We present AgentLens, a production-assessed benchmark for interactive code agents. Most code-agent benchmarks reduce a run to a single bit -- did the task pass? -- but the people who actually use these agents experience the entire trajectory: how the agent follows instructions, uses its tools, verifies its own work, recovers from mistakes, and talks to them along the way. AgentLens evaluates that whole trajectory. It pairs formal verification, where an objective check exists, with LLM-written t…
Pretrained video generative models are promising backbones for visuomotor control, but their imagined futures often drift from task intent and are not reliably action-conditional. As a result, these models can be difficult to use for planning or policy extraction. To address these limitations, we propose RoboTALES, a single-stage framework that learns task-aligned simulated futures and uses them to train robot policies. Our approach introduces two key innovations: (1) a hierarchical LLM-based p…
Coding agents increasingly generate pull requests (PRs) for real-world software issues, yet one-shot PR generation remains open-loop: the PR is proposed without systematic review, diagnosis, or revision. We introduce SWE-Review, a framework for closing this loop with agentic code review. Given an issue and an AI-generated PR, a reviewer agent explores the repository, decides whether the PR should be accepted, and provides structured feedback for revision. We evaluate this setting with our propo…
Most safety alignment work treats "detect the attack" as a text classification problem — does the prompt contain language the model's safety guardrails should catch. That assumption breaks down for LLM agents with real tool access. Here's a concrete case: take a known, public security vulnerability (a CVE), work out the sequence of tool calls that would exploit it, then have an LLM rewrite that a…
Accurate breast cancer classification from mammography requires effective integration of complementary information from craniocaudal (CC) and mediolateral oblique (MLO) views, which provide a more complete characterization of breast abnormalities. However, existing multi-view learning approaches typically rely on feature-level aggregation or single-stage cross-attention, which can entangle view-specific and shared representations and restrict interaction to limited network depths. To address th…
A new OpenAI report maps how AI could reshape jobs across the EU, highlighting which occupations may face automation, growth, or workflow changes.
A new OpenAI research paper shows how AI agents are transforming work, enabling longer, more complex tasks and expanding productivity across roles.
OpenAI helps build shared standards for advanced AI, supporting evaluation frameworks, safety practices, and global cooperation through the Appia Foundation.
Learn how Jason Liu uses Codex to preserve context, manage complex projects, and help work continue beyond a single prompt.
OpenAI launches the Partner Network, investing $150M to help global partners accelerate enterprise AI adoption, deployment, and transformation.
OpenAI introduces three Academy courses that help people build practical AI skills, create repeatable workflows, and apply agents in everyday work.
OpenAI plans to acquire Ona to expand Codex with secure, persistent cloud environments, enabling long-running AI agents across enterprise workflows.
OpenAI supports the EU Code of Practice on AI content transparency, advancing provenance standards and tools to help people understand AI-generated content.
Gemini 3.5 is built to help you execute complex, agentic workflows.
Gemma 4: Our most intelligent open models to date, purpose-built for advanced reasoning and agentic workflows.
We’re introducing a framework to measure progress toward AGI, and launching a Kaggle hackathon to build the relevant evaluations.