🚀 WELCOME TO METAMESH.BIZ +++ Meta teaching AI to deepfake your mouth movements in real-time because dubbing wasn't uncanny enough already +++ Someone actually built WASM airgap middleware to protect their Postgres from Llama 3's SQL dreams (paranoid but respect the hustle) +++ Small language models suddenly solving complex reasoning while we're still burning TPUs on the big ones +++ THE FUTURE OF AI IS SANDBOX-ISOLATED AND SPEAKING PERFECT MANDARIN WITH YOUR GRANDMOTHER'S LIPS +++ 🚀 •
🚀 WELCOME TO METAMESH.BIZ +++ Meta teaching AI to deepfake your mouth movements in real-time because dubbing wasn't uncanny enough already +++ Someone actually built WASM airgap middleware to protect their Postgres from Llama 3's SQL dreams (paranoid but respect the hustle) +++ Small language models suddenly solving complex reasoning while we're still burning TPUs on the big ones +++ THE FUTURE OF AI IS SANDBOX-ISOLATED AND SPEAKING PERFECT MANDARIN WITH YOUR GRANDMOTHER'S LIPS +++ 🚀 •
"Hi everyone,
I’ve been working in computer vision for several years, and over the past year I built X-AnyLabeling.
At first glance it looks like a labeling tool, but in practice it has evolved into something closer to a multimodal annotation ecosystem that connects labeling, AI inference, and ..."
"I’ve been working with multiple LLMs in long, sustained interactions, hundreds of turns, frequent domain switching (math, philosophy, casual context), and even switching base models mid-stream.
A consistent failure mode shows up regardless of model size or training quality:
identity and coherence ..."
💬 "Companies can't offer coherent models that don't fall behind or become unrealistic."
• "Coherence is not decreed by a central module, but emerges from the regulated interaction of all Custodians under the reference of the final value (V_f)."
"I wanted to let Llama 3 answer questions from my real Postgres DB.
I couldn’t bring myself to give it a direct connection. Even read-only felt
unsafe with PII and margins in the schema.
Most “AI SQL guardrails” rely on regex or JS SQL parsers. That felt flimsy —
especially with n..."
💬 "This is what access controls are for, indeed"
• "I trust that the database permissions will work a lot more than I trust that a piece of middleware that I wrote will work."
via Arxiv👤 Songyang Gao, Yuzhe Gu, Zijian Wu et al.📅 2025-12-11
⚡ Score: 7.3
"Large language models (LLMs) have achieved significant progress in solving complex reasoning tasks by Reinforcement Learning with Verifiable Rewards (RLVR). This advancement is also inseparable from the oversight automated by reliable verifiers. However, current outcome-based verifiers (OVs) are una..."
+++ OpenAI integrated skill-based function calling into ChatGPT and Codex, enabling document and spreadsheet manipulation. Apparently copying good ideas counts as shipping features now. +++
"Retrieval-Augmented Generation (RAG) systems often fail on multi-hop queries when the initial retrieval misses a bridge fact. Prior corrective approaches, such as Self-RAG, CRAG, and Adaptive-$k$, typically address this by \textit{adding} more context or pruning existing lists. However, simply expan..."
"Hi everyone.
I built a CLI tool called **Quorum** to stop relying on a single AI model. It orchestrates structured debates between agents to force them to fact-check each other.
**How I use it with Claude:** I usually set **Claude Opus** as the "Judge" or "Synthesizer" because of its strong reason..."
via Arxiv👤 Aileen Cheng, Alon Jacovi, Amir Globerson et al.📅 2025-12-11
⚡ Score: 6.7
"We introduce The FACTS Leaderboard, an online leaderboard suite and associated set of benchmarks that comprehensively evaluates the ability of language models to generate factually accurate text across diverse scenarios. The suite provides a holistic measure of factuality by aggregating the performa..."
"* GPT-OSS-120B-Eagle3-throughput is an **optimized speculative decoding module** built on top of the *OpenAI gpt-oss-120b* base model, designed to improve throughput during text generation.
* It uses NVIDIA’s **Eagle3 speculative decoding** approach with the Model Optimizer to predict a single draf..."
💬 Reddit Discussion: 37 comments
🐝 BUZZING
🎯 Model Performance • Model Enhancements • Community Engagement
💬 "It's unfortunately not supported in llama.cpp."
• "It is used for speculative decoding."
via Arxiv👤 Muhammad Umair Haider, Hammad Rizwan, Hassan Sajjad et al.📅 2025-12-11
⚡ Score: 6.6
"Circuit discovery aims to identify minimal subnetworks that are responsible for specific behaviors in large language models (LLMs). Existing approaches primarily rely on iterative edge pruning, which is computationally expensive and limited to coarse-grained units such as attention heads or MLP bloc..."
via Arxiv👤 Manurag Khullar, Utkarsh Desai, Poorva Malviya et al.📅 2025-12-11
⚡ Score: 6.6
"Large Language Models (LLMs) are increasingly deployed in high-stakes clinical applications in India. In many such settings, speakers of Indian languages frequently communicate using romanized text rather than native scripts, yet existing research rarely evaluates this orthographic variation using r..."
"With Mistral 3 and DeepSeek V3.2, we got two major open-weight LLMs this month already. I looked into DeepSeek V3.2 last week and just caught up with reading through the config of the Mistral 3 architecture in more detail.
Interestingly, based on [their official announcement post](https://mistr..."
💬 Reddit Discussion: 20 comments
🐝 BUZZING
🎯 Open-source architecture • Model performance comparison • Architectural innovations
💬 "If your competitors copy you but don't innovate, they'll stay 9 months behind you."
• "Using MoE makes sense for these large models so they can be sufficiently efficient for inference."
"Disclaimer: I work at an AI benchmarker and the screenshot is from our latest work.
We test AI models against the same set of questions and the disconnect between our measurements and what AI labs claim is widening.
For example, when it comes to hallucination rates, GPT-5.2 was like GPT-5.1 ..."
💬 Reddit Discussion: 17 comments
🐝 BUZZING
🎯 Measuring LLM Hallucination • Benchmarking LLM Performance • LLM Usage for Marketing Research
💬 "I find it hard to believe that Grok has the least hallucinations"
• "Interesting that your results are very different to my (admittedly unscientific) observations"
via Arxiv👤 Max Zimmer, Christophe Roux, Moritz Wagner et al.📅 2025-12-11
⚡ Score: 6.4
"The resource requirements of Neural Networks can be significantly reduced through pruning -- the removal of seemingly less important parameters. However, with the rise of Large Language Models (LLMs), full retraining to recover pruning-induced performance degradation is often prohibitive and classic..."
via Arxiv👤 Rebekka Görge, Sujan Sai Gannamaneni, Tabea Naeven et al.📅 2025-12-11
⚡ Score: 6.3
"Textual data used to train large language models (LLMs) exhibits multifaceted bias manifestations encompassing harmful language and skewed demographic distributions. Regulations such as the European AI Act require identifying and mitigating biases against protected groups in data, with the ultimate..."
"Dolphin-v2 is an enhanced universal document parsing model that substantially improves upon the original Dolphin.
Dolphin-v2 is built on **Qwen2.5-VL-3B** backbone with:
* Vision encoder based on Native Resolution Vision Transformer (NaViT)
* Autoregressive decoder for structured output generation..."
💬 "Isn't that Dolphin dead for over a year?"
• "What i'm actually curious about here is what makes a universal document parsing model different from a plain VLM."
"The video was created using Kling 2.6 model on Higgsfield, in total it took me 2 days ..."
💬 Reddit Discussion: 211 comments
😐 MID OR MIXED
🎯 AI and Media Landscape • Practical vs. CGI • Generational Shift
💬 "People are already fed up with AI after 3 years"
• "If / when they start using this to get certain shots done faster and cheaper, I fully expect them to downplay the involvement video generation played in a similar way"
"Olmo 3.1 32B Think and Olmo 3.1 32B Instruct are the newest 32-billion-parameter models in the Olmo family, each optimized for different yet complementary use cases.
* The **Think model** is a deep-reasoning specialist, trained with extended reinforcement learning on the Dolci-Think-RL dataset to..."
💬 Reddit Discussion: 18 comments
🐝 BUZZING
🎯 Open Source Models • Model Improvements • Instruction Capabilities
💬 "Olmo models are truly open source and getting better and better."
• "Will improve this on future models."
"Hey all,
So I am sure you already know the ICLR drama this year + since reciprocal reviewing, authors have struggled with reviews. Well, I scraped public OpenReview metadata for ICLR 2018–2025 and did a simple analysis of acceptance vs (i) review score, (ii) primary area, and (iii) year to see if a..."
via Arxiv👤 George Yakushev, Nataliia Babina, Masoud Vahid Dastgerdi et al.📅 2025-12-11
⚡ Score: 6.1
"Many state-of-the-art LLMs are trained to think before giving their answer. Reasoning can greatly improve language model capabilities and safety, but it also makes them less interactive: given a new input, a model must stop thinking before it can respond. Real-world use cases such as voice-based or..."
🎯 AI limitations • Prompting techniques • Iterative workflow
💬 "It's very difficult to know the limits of current AI methods."
• "Focus on the little improvements, don't skip design, and don't sacrifice quality!"