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22 results for “MoE”
Introducing OlmoEarth embeddings: Custom embedding exports from OlmoEarth Studio for downstream analysis
Hugging Face announced OlmoEarth embeddings, a new feature allowing users to export custom embeddings from its OlmoEarth Studio platform for downstream analysis.
Aug 12, 2026
TEXAS: Task-Expert-Aware Supervision for Downstream Mixture-of-Experts LLM Adaptation
A new research method called TEXAS improves fine-tuning of Mixture-of-Experts (MoE) LLMs by using correctness-conditioned expert activation patterns to guide token-level supervision, yielding consistent performance gains across models and benchmarks.
Aug 10, 2026
Beyond Routing Weights: Faithful Response-Level Interpretation of Mixture-of-Experts Reward Models via Contribution Contrast
Researchers introduced CoCo, a new response-level interpretation method for Mixture-of-Experts reward models that improves interpretability by analyzing contribution contrasts between chosen and rejected responses, rather than relying solely on routing weights.
Aug 10, 2026
EntropyMoE: Entropy-Aware Sparse Expert Routing for Tokenizer-Free LLMs
EntropyMoE is a new Mixture-of-Experts architecture for byte-level, tokenizer-free LLMs that routes computation per dynamic byte patch using entropy as a routing signal, improving compression efficiency without sacrificing downstream task accuracy.
Aug 10, 2026
Show HN: Maple-Preview – ternary 20B MoE running at 120 tok/s on a iPhone
A forum post announces 'Maple-Preview', a claimed ternary 20B MoE (Mixture of Experts) AI model purportedly running at 120 tokens per second on an iPhone, with no technical documentation, benchmark validation, or verifiable evidence provided.
Aug 5, 2026
Hierarchical Copula-Gumbel-Top-\texorpdfstring{$K$}{K} Routing: Two-Sided Dependence Control for Frozen Mixture-of-Experts at Fixed Per-Token Routing Laws
A new mathematical routing method for mixture-of-experts (MoE) models introduces controlled dependence between tokens’ expert selections while preserving per-token routing laws and enabling training via a lightweight controller over frozen model weights.
Aug 3, 2026
OpenAI announces its "next major model" Astra by dropping ten previously unsolved math solutions
OpenAI announced a new model family named 'Astra'—described as enabling multi-agent, long-duration problem solving—with no technical documentation, release timeline, or verifiable evidence beyond an unattributed claim of solving ten previously unsolved math problems.
Aug 1, 2026
Sam Altman demoed OpenAl's unreleased "Astra" model to policymakers this week
An unverified Reddit post claims Sam Altman demoed OpenAI's unreleased 'Astra' AI model to U.S. policymakers in Washington, D.C., citing an Information.com briefing as source.
Aug 2, 2026
Sources: OpenAI demoed a new "Astra" AI model family to US policymakers and regulators this week, touting its improved abilities to complete long-running tasks (The Information)
OpenAI privately demonstrated an unreleased AI model family named 'Astra' to US policymakers and regulators, emphasizing its enhanced capability for long-running tasks as part of pre-launch government engagement.
Aug 1, 2026
The OlmoEarth Platform: Geospatial inference at planetary scale
Hugging Face announced the OlmoEarth platform, a new open geospatial AI model suite designed for planetary-scale Earth observation inference, positioning it as a foundational tool for global environmental monitoring and climate modeling.
Jul 28, 2026
MoE$^2$-LoRA: When MoE Models Meet MoE-style Low-Rank Adaptation
A new parameter-efficient fine-tuning method called MoE²-LoRA is introduced to improve adaptation of Mixture-of-Experts language models by dynamically routing low-rank adapters using pretrained router signals and sharing a global expert pool across layers.
Jul 27, 2026
Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations
Researchers propose EAACD, a new contrastive decoding method tailored for mixture-of-experts (MoE) LLMs that leverages expert activation differences in higher layers to reduce hallucinations on QA tasks, outperforming baselines across four datasets.
Jul 24, 2026
Multi-level context Modeling for consistent expert selection in Mixture-of-Experts
Researchers propose MCF-MOE, a new Mixture-of-Experts routing framework that improves expert selection consistency by fusing multi-level contextual signals across Transformer layers, addressing instability in existing MoE models.
Jul 21, 2026
German SooFi team launches Soofi S 30B-A3B , an open-source Mixture-of-Experts (MoE) hybrid Mamba–Transformer foundation model for German and English.
A German research team released an open-source Mixture-of-Experts (MoE) hybrid Mamba–Transformer language model supporting German and English, named Soofi S 30B-A3B.
Jul 19, 2026
Thinking Machines Lab debuts Inkling, an open-weight MoE model with 975B total and 41B active parameters, trained to be broad rather than optimized for one area (Thinking Machines Lab)
Thinking Machines Lab released Inkling, an open-weight Mixture-of-Experts (MoE) large language model with 975B total parameters and 41B active per inference, positioned as broadly capable rather than task-specialized.
Jul 16, 2026
European Commission President Ursula von der Leyen says the bloc is set to propose a "social media start date for minors", with a proposal after a summer break (Barbara Moens/Financial Times)
The European Commission plans to propose age-graded access thresholds for minors' social media use, framing it as a child safety response ahead of formal legislative drafting.
Jul 13, 2026
Moen and Stand Insurance Launch Program to Help Homeowners Cut Water Damage Risk and Insurance Costs
Moen and Stand Insurance launched a program linking Moen's smart water shutoff technology to insurance premium discounts, creating the first direct financial incentive for homeowners to adopt active leak prevention.
Jul 9, 2026
MoEngage y Boldest anuncian una alianza estratégica
MoEngage and Boldest announced a strategic partnership to deliver cognitive intelligence–powered customer engagement solutions for telecom operators, with no operational details, technical specifications, or evidence of integration or deployment provided.
Published Jul 3, 2026 · Analyzed Jul 6, 2026
On the Utility and Factual Reliability of Pruned Mixture-of-Experts Models in the Biomedical Domain
A new arXiv preprint investigates how pruning Mixture-of-Experts (MoE) models affects factual reliability in biomedical AI, finding that moderate pruning preserves utility but increases hallucination risk at extreme ratios—and that reliability degrades sharply outside the trained domain.
Published Jul 3, 2026 · Analyzed Jul 6, 2026
the trust layer is the real product
A product team observed that user retention for their AI tool improved more from explicitly demarcating AI-human handoff points than from model upgrades, revealing trust—not accuracy—as the critical bottleneck in real-world AI adoption.
Published Jul 2, 2026 · Analyzed Jul 6, 2026
Multi-scale Mixture of World Models for Embodied Agents in Evolving Environments
Researchers propose a new framework for embodied agents to adapt knowledge in changing environments.
Published Jul 2, 2026 · Analyzed Jul 5, 2026
Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding
Ornith-1.0 is a self-scaffolding LLM for agentic coding released by DeepReinforce.
Published Jun 29, 2026 · Analyzed Jul 5, 2026