csinva / interpretable-embeddingsLinks
Interpretable text embeddings by asking LLMs yes/no questions (NeurIPS 2024)
☆36Updated 6 months ago
Alternatives and similar repositories for interpretable-embeddings
Users that are interested in interpretable-embeddings are comparing it to the libraries listed below
Sorting:
- ☆117Updated 10 months ago
- ☆66Updated 2 years ago
- ☆94Updated last year
- ☆93Updated 11 months ago
- Code for "Reasoning to Learn from Latent Thoughts"☆104Updated 2 months ago
- ☆23Updated 4 months ago
- Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision☆120Updated 8 months ago
- Official repository for our paper, Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Mode…☆16Updated 6 months ago
- ☆93Updated 3 months ago
- Exploring the Limitations of Large Language Models on Multi-Hop Queries☆25Updated 3 months ago
- Lightweight Adapting for Black-Box Large Language Models☆22Updated last year
- Function Vectors in Large Language Models (ICLR 2024)☆167Updated last month
- ☆124Updated 6 months ago
- Code for the paper "VinePPO: Unlocking RL Potential For LLM Reasoning Through Refined Credit Assignment"☆159Updated last week
- [ICLR 2025] Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization☆28Updated 4 months ago
- Data and code for the Corr2Cause paper (ICLR 2024)☆105Updated last year
- ☆40Updated last year
- Sparse Autoencoder Training Library☆52Updated last month
- A library for efficient patching and automatic circuit discovery.☆65Updated last month
- ☆85Updated last year
- ☆97Updated 11 months ago
- ☆48Updated 3 weeks ago
- [ICML 2025] Flow of Reasoning: Training LLMs for Divergent Reasoning with Minimal Examples☆89Updated last week
- ☆83Updated 9 months ago
- Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implici…☆106Updated last year
- ☆54Updated 2 weeks ago
- [NAACL'25 Oral] Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering☆58Updated 6 months ago
- The accompanying code for "Transformer Feed-Forward Layers Are Key-Value Memories". Mor Geva, Roei Schuster, Jonathan Berant, and Omer Le…☆91Updated 3 years ago
- Code release for "Debating with More Persuasive LLMs Leads to More Truthful Answers"☆107Updated last year
- maze datasets for investigating OOD behavior of ML systems☆48Updated last week