·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Vertu wants executives to pay $6,880 for an AI agent — here’s how it actually performs4h◆Databricks hits $188B valuation, extending its run as AI’s favorite second act5h◆The Zoom hack that says, ‘Don’t record me’5h◆Agility Robotics plants its flag in Tesla’s backyard6h◆AI-driven memory crunch jolts India’s smartphone market7h◆TikTok is testing an AI likeness detection tool7h◆How Apple’s big lawsuit could disrupt OpenAI’s IPO plans9h◆Apple’s plot to crush OpenAI9h◆Fine-tune video and image models at scale with NVIDIA NeMo Automodel and 🤗 Diffusers11h◆Patreon stops asking AI bots not to scrape — and starts blocking them11h◆Apple’s lawsuit couldn’t come at a worse time for OpenAI13h◆Why the first GPU financiers are turning to inference chips in a $400 million deal15h◆A scorecard for the AI age17h◆The risk of weather data sabotage is rising18h◆The Steering Budget: Examples beat Knobs23h◆Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs23h◆RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination23h◆When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models23h◆SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation23h◆ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System23h◆Vertu wants executives to pay $6,880 for an AI agent — here’s how it actually performs4h◆Databricks hits $188B valuation, extending its run as AI’s favorite second act5h◆The Zoom hack that says, ‘Don’t record me’5h◆Agility Robotics plants its flag in Tesla’s backyard6h◆AI-driven memory crunch jolts India’s smartphone market7h◆TikTok is testing an AI likeness detection tool7h◆How Apple’s big lawsuit could disrupt OpenAI’s IPO plans9h◆Apple’s plot to crush OpenAI9h◆Fine-tune video and image models at scale with NVIDIA NeMo Automodel and 🤗 Diffusers11h◆Patreon stops asking AI bots not to scrape — and starts blocking them11h◆Apple’s lawsuit couldn’t come at a worse time for OpenAI13h◆Why the first GPU financiers are turning to inference chips in a $400 million deal15h◆A scorecard for the AI age17h◆The risk of weather data sabotage is rising18h◆The Steering Budget: Examples beat Knobs23h◆Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs23h◆RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination23h◆When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models23h◆SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation23h◆ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System23h◆
News/Stateful Token Reduction for Long-Video Hybrid VLMs
arxiv
PublishedJuly 2, 2026 at 4:00 AM
—neutral

Stateful Token Reduction for Long-Video Hybrid VLMs

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2603.00198v2 Announce Type: replace-cross Abstract: Token reduction accelerates long-video vision--language models (VLMs), but existing methods target Transformers, where reduction is treated as token pruning. We study token reduction in hybrid Mamba--Transformer VLMs and find that it is \emph

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivThe Steering Budget: Examples beat Knobs23harxivPolestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs23harxivRxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination23harxivWhen a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models23h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews