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SenseNova

7 articles · Page 1 of 1
Machine Heart
Machine Heart
Nov 2, 2026 · Artificial Intelligence

MT Forcing: Stabilizing Multi-Turn Image Editing with Single-Turn DMD and Teacher Forcing

Researchers from SenseTime, HKUST MMLab, Stanford, and Tsinghua propose MT Forcing, a training method combining Single-Turn DMD and Teacher-Forcing Guidance to solve quality degradation and content drift in multi-turn image editing, achieving significant improvements in instruction following, content consistency, and geometric stability over 8 editing turns on SenseNova models.

Autoregressive diffusionComputer VisionDistribution matching distillation
0 likes · 10 min read
MT Forcing: Stabilizing Multi-Turn Image Editing with Single-Turn DMD and Teacher Forcing
Machine Heart
Machine Heart
Jul 21, 2026 · Artificial Intelligence

How SenseTime’s New Multimodal Architecture Redefines Unified AI Foundations

The article analyzes SenseTime’s recent SenseNova U1 Pro and SenseNova‑Vision releases, detailing their NEO‑unify architecture, unified multimodal training, extensive SN‑VC‑50M dataset, benchmark breakthroughs, and the broader shift toward a single, long‑term, agentic AI base model.

AI ArchitectureNEO-unifySN-VC-50M dataset
0 likes · 10 min read
How SenseTime’s New Multimodal Architecture Redefines Unified AI Foundations
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Jul 20, 2026 · Artificial Intelligence

Why Multimodal AI Is the Next Battlefield After Coding – Insights from SenseTime’s Lin Dahua

In a WAIC interview, SenseTime’s chief scientist Lin Dahua explains why multimodal AI, embodied in the native‑unified NEO‑unify architecture and the commercial‑grade SenseNova U1 Pro, is poised to surpass coding as the next competitive frontier, highlighting technical challenges, data efficiency, design‑focused benchmarks, and a 70% delivery‑rate claim.

AILarge Language ModelsNEO-unify
0 likes · 18 min read
Why Multimodal AI Is the Next Battlefield After Coding – Insights from SenseTime’s Lin Dahua
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Jul 19, 2026 · Artificial Intelligence

Why Multimodal AI Is the Next Battlefield After Coding, According to SenseTime’s Lin Dahua

In an interview at the 2026 WAIC conference, SenseTime chief scientist Lin Dahua explains why multimodal AI—driven by the native unified NEO‑unify architecture and embodied in the commercial‑grade SenseNova U1 Pro with a 70% delivery rate—represents the next decisive frontier beyond AI coding, highlighting technical challenges, market trends, and future research directions.

AI model architectureNEO-unifySenseNova
0 likes · 20 min read
Why Multimodal AI Is the Next Battlefield After Coding, According to SenseTime’s Lin Dahua
SuanNi
SuanNi
May 29, 2026 · Artificial Intelligence

SenseNova-U1-8B-MoT-Infographic: Academic Charts, Posters, Recipes

The SenseNova-U1-8B-MoT-Infographic model dramatically improves AI‑generated infographics by enhancing dense‑text rendering, layout stability, and chart accuracy through targeted data, extended mid‑training, and reinforcement‑learning fine‑tuning, achieving top scores on BizGenEval and IGenBench and surpassing many commercial rivals.

AI modelBenchmarkReinforcement Learning
0 likes · 9 min read
SenseNova-U1-8B-MoT-Infographic: Academic Charts, Posters, Recipes
DataFunTalk
DataFunTalk
May 23, 2026 · Industry Insights

How AI Companies Can Become Anti‑Fragile in the Token Economy

Amid the surge of token‑driven revenue models, AI firms face rising costs and price hikes; the article analyzes how companies like DeepSeek and SenseNova lower token consumption through technical innovation, adopt productivity‑focused strategies, and build anti‑fragile business models to sustain growth despite market volatility.

AI Business ModelAnti-FragilityDeepSeek
0 likes · 14 min read
How AI Companies Can Become Anti‑Fragile in the Token Economy
Data Party THU
Data Party THU
Apr 26, 2026 · Industry Insights

Multimodal Perception and AI Fusion: Highlights from Tsinghua’s 9th Big Data Intelligent Lecture

The 9th Tsinghua Big Data Intelligent Lecture gathered leading scholars and industry experts to showcase cutting‑edge research on multimodal perception, embodied intelligence, spatial AI, large‑model multimodal systems, and industrial time‑series databases, emphasizing their technical depth and real‑world impact.

GLM5V TurboSenseNovaartificial intelligence
0 likes · 8 min read
Multimodal Perception and AI Fusion: Highlights from Tsinghua’s 9th Big Data Intelligent Lecture