·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Run a vLLM Server on HF Jobs in One Command-172m◆Patronus AI lands $50M to build ‘digital worlds’ that stress-test AI agents49m◆Anthropic’s Claude is winning over paid consumers, a market owned by ChatGPT3h◆General Intuition’s $2.3B bet that video games can train AI agents for the real world4h◆Databricks’ former AI chief thinks he can cut AI’s power bill by 1,000x4h◆Which tokens does a hybrid model predict better?4h◆Our latest Google Finance upgrades, including a new app5h◆Netris raises $15M Series A from a16z to help AI neoclouds go live faster6h◆Repositioning retail for the AI era6h◆2 days left to save up to $190: Join 1,000+ founders and investors at TechCrunch Founder Summit7h◆Adobe acquires image and video enhancement tool maker Topaz Labs7h◆Amazon ups India bet with fresh $13B AI infrastructure investment9h◆Ford had to hire back former engineers to fix mistakes made by its automated systems9h◆Facebook’s Creator Studio has been revived as an AI companion app12h◆Can Aggregate Invariants Accelerate Continuous Subgraph Matching? Limits, Laws, and a Dynamic Spectral Index17h◆ScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling17h◆Critique of Agent Model17h◆LemonHarness Technical Report17h◆The Measurable Majority17h◆Fast and Slow Variational Continual Learning17h◆Run a vLLM Server on HF Jobs in One Command-172m◆Patronus AI lands $50M to build ‘digital worlds’ that stress-test AI agents49m◆Anthropic’s Claude is winning over paid consumers, a market owned by ChatGPT3h◆General Intuition’s $2.3B bet that video games can train AI agents for the real world4h◆Databricks’ former AI chief thinks he can cut AI’s power bill by 1,000x4h◆Which tokens does a hybrid model predict better?4h◆Our latest Google Finance upgrades, including a new app5h◆Netris raises $15M Series A from a16z to help AI neoclouds go live faster6h◆Repositioning retail for the AI era6h◆2 days left to save up to $190: Join 1,000+ founders and investors at TechCrunch Founder Summit7h◆Adobe acquires image and video enhancement tool maker Topaz Labs7h◆Amazon ups India bet with fresh $13B AI infrastructure investment9h◆Ford had to hire back former engineers to fix mistakes made by its automated systems9h◆Facebook’s Creator Studio has been revived as an AI companion app12h◆Can Aggregate Invariants Accelerate Continuous Subgraph Matching? Limits, Laws, and a Dynamic Spectral Index17h◆ScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling17h◆Critique of Agent Model17h◆LemonHarness Technical Report17h◆The Measurable Majority17h◆Fast and Slow Variational Continual Learning17h◆
News/Can Scale Save Us From Plasticity Loss in Large Language Models?
arxiv
PublishedJune 25, 2026 at 4:00 AM
—neutral

Can Scale Save Us From Plasticity Loss in Large Language Models?

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

arXiv:2606.24752v1 Announce Type: new Abstract: The loss of plasticity - the ability of a network to learn new information after having already learned older information - is a fundamental challenge in creating artificial neural networks capable of continual learning. Although this phenomenon has be

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
arxivCan Aggregate Invariants Accelerate Continuous Subgraph Matching? Limits, Laws, and a Dynamic Spectral Index17harxivScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling17harxivCritique of Agent Model17harxivLemonHarness Technical Report17h
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