Are LLMs being trained using LessWrong text? — LessWrong
AI

Are LLMs being trained using LessWrong text? — LessWrong

I wonder if there’s a clear evidence that LessWrong text has been included in LLM training. Claude seems generally aware of LessWrong, but it’s difficult to distinguish between “this model has been trained on text that mentions LessWrong” and “this model has been trained on text from LessWrong” Related discussion here, about preventing inclusion:

A Simple Explanation of AGI Risk — LessWrong
AI

A Simple Explanation of AGI Risk — LessWrong

Notes from a talk originally given at my alma mater I went to Grinnell College for my undergraduate degree. For the 2025 reunion event, I agreed to speak on a panel about AI. I like the talk I gave because I think it’s a good “101” intro to AI risk, aimed at educated laypeople. I’m also

Are LLMs being trained using LessWrong text? — LessWrong
AI

Problematic Professors — LessWrong

Don’t judge a principle by its professors—look to its practitioners. “Professor” is an interesting word. At one point in my professional life, I had the opportunity to teach college classes. I often corrected students who called me “Professor Eggs,” telling them I was just “Mr. Eggs.” “Professor” was a title and a high status I

Bootstrapping Audio-Language Alignment with Synthetic Data
AI

Bootstrapping Audio-Language Alignment with Synthetic Data

[Submitted on 26 May 2025 (v1), last revised 30 Jun 2025 (this version, v2)] View a PDF of the paper titled From Alignment to Advancement: Bootstrapping Audio-Language Alignment with Synthetic Data, by Chun-Yi Kuan and Hung-yi Lee View PDF HTML (experimental) Abstract:Audio-aware large language models (ALLMs) have recently made great strides in understanding and processing

Bootstrapping Audio-Language Alignment with Synthetic Data
AI

Autonomy by Design: Preserving Human Autonomy in AI Decision-Support

arXiv:2506.23952v1 Announce Type: cross Abstract: AI systems increasingly support human decision-making across domains of professional, skill-based, and personal activity. While previous work has examined how AI might affect human autonomy globally, the effects of AI on domain-specific autonomy — the capacity for self-governed action within defined realms of skill or expertise — remain understudied. We

Bootstrapping Audio-Language Alignment with Synthetic Data
AI

ReMem: Mutual Information-Aware Fine-tuning of Pretrained Vision Transformers for Effective Knowledge Distillation

arXiv:2506.23041v1 Announce Type: cross Abstract: Knowledge distillation from pretrained visual representation models offers an effective approach to improve small, task-specific production models. However, the effectiveness of such knowledge transfer drops significantly when distilling from strong models that are pretrained in a large scale. In this paper, we address this challenge for pretrained Vision Transformers (ViTs)

Bootstrapping Audio-Language Alignment with Synthetic Data
AI

Natural Language Exploration of Hardware Designs and Libraries

[Submitted on 17 Jul 2024 (v1), last revised 29 Jun 2025 (this version, v3)] View a PDF of the paper titled ChipXplore: Natural Language Exploration of Hardware Designs and Libraries, by Manar Abdelatty and 2 other authors View PDF HTML (experimental) Abstract:Hardware design workflows rely on Process Design Kits (PDKs) from different fabrication nodes, each

Bootstrapping Audio-Language Alignment with Synthetic Data
AI

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead

arXiv:2506.23762v1 Announce Type: cross Abstract: The rapid advancement of large language models (LLMs) has redefined artificial intelligence (AI), pushing the boundaries of AI research and enabling unbounded possibilities for both academia and the industry. However, LLM development faces increasingly complex challenges throughout its lifecycle, yet no existing research systematically explores these challenges and solutions from

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