Aimed at folks seeking rigorous conceptual and practical tools for designing reasoning systems. See you at ESSAI 2026!
#NeuralSymbolic #LLM #ReasoningModels
7
Search
MIT Tech Review's #1 breakthrough tech of 2026: reasoning models — AIs that think through problems step by step. Not just faster answers. Smarter ones. This changes everything. #AI #ReasoningModels #MITTechReview
18
Deploying reasoning models at scale? Compute waste from miscalibrated thinking adds up.
ReBalance is plug-and-play — test before your next deployment.
#AI #LLMs #ReasoningModels #MLEngineering #DeepLearning
Follow @MorelMatth66161 — more threads like this.
2
If trainers can’t solve it, models won’t either.
Logic is the real product.
🔗aqusag.com/blog/aqusag-te…J
#AIInnovation #DeepLearning #ReasoningModelsY
11
🧠 Microsoft apuesta con su modelo Phi-4: más grande no siempre es mejor
Desafiando la tendencia de modelos masivos, Microsoft presenta su eficiente Phi-4.
thenewstack.io/with-its-lates…w
#AI #MachineLearning #ReasoningModels #RoxsRoss
79
Reasoning Models Can't Hide Their Thinking - OpenAI Study
OpenAI's CoT-Control benchmark shows frontier reasoning models score 0.
#AiSafety #ReasoningModels
1
21
LLM “reasoning” isn’t a diary. It’s chemistry: bonds between steps. This paper argues distillation fails when you copy words instead of the topology—and MOLE-SYN tries to transfer the bond pattern go.abvx.xyz/ewbg62
#LongCoT #ReasoningModels #ModelDistillation #SyntheticData
The Molecular Structure of Thought: Why Long Chain-of-Thought Isn’t “Text” — It’s Topology
Why distillation fails, why “reasoning traces” are a moat, and how MOLE-SYN tries to copy the shape of thought — not the words.
From abvcreative.medium.com 1
51
If trainers can’t solve it, models won’t either.
Logic is the real product.
🔗aqusag.com/blog/aqusag-te…J
#AIInnovation #DeepLearning #ReasoningModelsi
16
🧠 Los modelos de razonamiento no controlan su cadena de pensamientos, y eso es bueno
OpenAI presenta CoT-Control, un hallazgo clave para la seguridad de la IA.
openai.com/index/reasonin…C
#ReasoningModels #AISafety #CoT #RoxsRoss
Reasoning models struggle to control their chains of thought, and that’s good
OpenAI introduces CoT-Control and finds reasoning models struggle to control their chains of thought, reinforcing monitorability as an AI safety safeguard.
From openai.com 1
2
92
Presenting CONTEXTUAL DRAG 🚨
Humans could benefit from incorrect previous attempts and avoid making the same mistakes, but reasoning models are dragged toward similar errors (even when explicitly knowing the attempts are incorrect!)
Work@PrincetonPLI
#LLM #ReasoningModels
Humans anchor on the first piece of information they receive. Do reasoning models escape this bias?
We uncover Contextual Drag: errors in context bias subsequent reasoning toward similar mistakes.
It persists even if the error has been recognized via reasoning.
4
226
Why 'Reasoning Models' are changing the automation game in 2026. 🧠🌐🛠️
It's no longer just about text; it's about logic and decision-making power.
Read the model report smartflowslab.com3Tq. #ReasoningModels #AIInnovation #FutureTech #BusinessAgentkDG
Full preprint, all equations, three reference Python scripts + GitHub Release v1.0.0 are here:
→ zenodo.org/records/188028…
Would love thoughts from the reasoning/agent crowd 👇
#LLM #ReasoningModels #AgenticAI #AdaptiveReasoning
1
117
What if symbolic reasoning wasn't a module bolted onto a neural network, but an emergent property of a multi-scale graph walk?
Here's a conceptual article on such an architecture.
medium.com/@ravi92sr/a-hi…
#neuro-symbolic #AIArchitecture #ReasoningModels #LLMs #resea
A Hierarchical, Multi-Scale Graph Architecture for Explainable Topological AI
Abstract
From medium.com 8
🚀 Mercury 2 boasts the fastest reasoning LLM for instant prod AI. Crucial for high-performance, real-time agent deployments. Where does LLM speed rank for your AI agent needs?
#ReasoningModels #AIEngineering
�producthunt.com/products/mercu…4x0
19
⚡ Mercury 2 claims fastest LLM reasoning via diffusion. This could significantly boost AI agent performance in dev tools. How crucial is reasoning speed for your current dev workflows?
#ReasoningModels #AIEngineering
🔗inceptionlabs.ai/blog/introduci…0e
35
🧠 ByteDance maps "molecular bonds" for stable long CoT reasoning. Crucial for robust, long-chain reasoning in production agents. How do you tackle long CoT stability in your AI agents?
#ReasoningModels #AIDevTools
�marktechpost.com/2026/02/22/for…B1m
11
🧠 Gemini 3.1 Pro hits 1M token context & 77.1% ARC-AGI-2 reasoning. A game-changer for building robust, long-running AI agents. What complex problems are you solving with agentic systems now?
#ReasoningModels #AIEngineering
�marktechpost.com/2026/02/19/goo…UuW
42