·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Why AMI Labs’ Alexandre LeBrun won’t call his AI ‘AGI’ or ‘superintelligence’1h◆Moonshot’s upcoming Kimi 3 is expected to close the gap with Anthropic’s Opus 4.81h◆Apple Intelligence approved for launch in China with Alibaba and Baidu2h◆Claude can now use your 1Password credentials for you3h◆Google ordered to open Android and Search to rivals in Europe3h◆Newer Models, Same Advantage4h◆Computer cops5h◆Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling12h◆SemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests12h◆MASPRM: Multi-Agent System Process Reward Model12h◆Delving into the Temporal Challenges of Unified Video Protection Against Image-to-Video and Fine-Tuning-based Customization12h◆A plug-and-play approach with fast uncertainty quantification for weak lensing mass mapping12h◆FastCentNN: Accelerating Centroid Neural Network with Entropy Proxy12h◆Cortical-SSM: A Deep State Space Model for Motor Imagery Decoding from EEG Signals12h◆Avoiding unsafe sets when training with Langevin Dynamics12h◆Set-shifting Behavioral Test for Harnessed Agents12h◆AIMO Interpretability Challenge12h◆The Perplexity Trap: When Patent Law Makes Human Writing Look Like AI12h◆The Refusal Residue: When Probes Catch Alignment Faking and When They Don't12h◆ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL12h◆Why AMI Labs’ Alexandre LeBrun won’t call his AI ‘AGI’ or ‘superintelligence’1h◆Moonshot’s upcoming Kimi 3 is expected to close the gap with Anthropic’s Opus 4.81h◆Apple Intelligence approved for launch in China with Alibaba and Baidu2h◆Claude can now use your 1Password credentials for you3h◆Google ordered to open Android and Search to rivals in Europe3h◆Newer Models, Same Advantage4h◆Computer cops5h◆Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling12h◆SemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests12h◆MASPRM: Multi-Agent System Process Reward Model12h◆Delving into the Temporal Challenges of Unified Video Protection Against Image-to-Video and Fine-Tuning-based Customization12h◆A plug-and-play approach with fast uncertainty quantification for weak lensing mass mapping12h◆FastCentNN: Accelerating Centroid Neural Network with Entropy Proxy12h◆Cortical-SSM: A Deep State Space Model for Motor Imagery Decoding from EEG Signals12h◆Avoiding unsafe sets when training with Langevin Dynamics12h◆Set-shifting Behavioral Test for Harnessed Agents12h◆AIMO Interpretability Challenge12h◆The Perplexity Trap: When Patent Law Makes Human Writing Look Like AI12h◆The Refusal Residue: When Probes Catch Alignment Faking and When They Don't12h◆ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL12h◆
News/CreativityNeuro: Steering Language Model Weights to Improve Divergent Thinking and Reduce Mode Collapse
arxiv
PublishedJuly 3, 2026 at 4:00 AM
—neutral

CreativityNeuro: Steering Language Model Weights to Improve Divergent Thinking and Reduce Mode Collapse

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

arXiv:2607.01433v1 Announce Type: new Abstract: Divergent thinking is a crucial aspect of creativity, yet large language models (LLMs) tend to consistently generate similar responses to open-ended questions, in what has been termed the artificial hivemind effect. Here, we introduce CreativityNeuro,

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
arxivMulti-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling12harxivSemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests12harxivMASPRM: Multi-Agent System Process Reward Model12harxivDelving into the Temporal Challenges of Unified Video Protection Against Image-to-Video and Fine-Tuning-based Customization12h
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