·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Theker just raised $85M to build the factory robot that doesn’t specialize in anything1h◆Jeff Bezos’s Prometheus raises $12B to build an ‘artificial general engineer’ for the physical world1h◆SpaceX officially prices shares at $135 in the largest IPO ever6h◆Our new community investments in Virginia support local jobs and expand energy affordability.6h◆SpaceX SPV investors won’t know their true holdings until post-IPO lock-ups lift6h◆Amazon’s data centers used 2.5 billion gallons of water last year9h◆Deezer’s new tool can identify AI music from Spotify, Apple Music, and others10h◆Pool’s new app turns your screenshots into something useful11h◆DoorDash’s new AI chatbot lets you order with prompts and photos12h◆Anthropic apologizes for invisible Claude Fable guardrails15h◆Google DeepMind is worried about what happens when millions of agents start to interact15h◆Deezer launches an AI music detector for other streaming services18h◆Opendoor’s India exit is fueling a bigger conversation about AI and outsourcing22h◆MODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning22h◆Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!22h◆ARGUS: Stacked Multi-View Identity Mosaic Injection for Subject-Preserving Video Generation22h◆Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Solutions22h◆The Impossibility of Eliciting Latent Knowledge22h◆Mapping Scientific Literature with Large Language Models and Topic Modeling22h◆Grounding Computer Use Agents on Human Demonstrations22h◆Theker just raised $85M to build the factory robot that doesn’t specialize in anything1h◆Jeff Bezos’s Prometheus raises $12B to build an ‘artificial general engineer’ for the physical world1h◆SpaceX officially prices shares at $135 in the largest IPO ever6h◆Our new community investments in Virginia support local jobs and expand energy affordability.6h◆SpaceX SPV investors won’t know their true holdings until post-IPO lock-ups lift6h◆Amazon’s data centers used 2.5 billion gallons of water last year9h◆Deezer’s new tool can identify AI music from Spotify, Apple Music, and others10h◆Pool’s new app turns your screenshots into something useful11h◆DoorDash’s new AI chatbot lets you order with prompts and photos12h◆Anthropic apologizes for invisible Claude Fable guardrails15h◆Google DeepMind is worried about what happens when millions of agents start to interact15h◆Deezer launches an AI music detector for other streaming services18h◆Opendoor’s India exit is fueling a bigger conversation about AI and outsourcing22h◆MODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning22h◆Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!22h◆ARGUS: Stacked Multi-View Identity Mosaic Injection for Subject-Preserving Video Generation22h◆Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Solutions22h◆The Impossibility of Eliciting Latent Knowledge22h◆Mapping Scientific Literature with Large Language Models and Topic Modeling22h◆Grounding Computer Use Agents on Human Demonstrations22h◆
Tag

#transformer

3 articles tagged #transformer

arxivJun 1bullish

RayDer: Scalable Self-Supervised Novel View Synthesis from Real-World Video

arXiv:2605.31535v1 Announce Type: cross Abstract: Self-supervised novel view synthesis (NVS) remains challenging to scale, despite the abundance of video data, largely due to the brittleness of training on realistic videos and the hard-to-predict scaling behavior of multi-network system designs. We

RA1 model#computer-vision#self-supervised#transformerRead on arxiv →
arxivMay 14bullish

ASAP: Amortized Doubly-Stochastic Attention via Sliced Dual Projection

arXiv:2605.12879v1 Announce Type: new Abstract: Doubly-stochastic attention has emerged as a transport-based alternative to row-softmax attention, with recent Transformer variants using it to reduce attention sinks and rank collapse while improving performance. In this family, the standard approach

SIAS2 models#transformer#attention#machine-learningRead on arxiv →
arxivApr 6bullish

Contrastive Language-Colored Pointmap Pretraining for Unified 3D Scene Understanding

arXiv:2604.02546v1 Announce Type: cross Abstract: Pretraining 3D encoders by aligning with Contrastive Language Image Pretraining (CLIP) has emerged as a promising direction to learn generalizable representations for 3D scene understanding. In this paper, we propose UniScene3D, a transformer-based e

OPUN2 models#computer-vision#3d-scene-understanding#transformerRead on arxiv →
HomeModelsNews