gregorbachmann / Next-Token-FailuresLinks
☆106Updated last year
Alternatives and similar repositories for Next-Token-Failures
Users that are interested in Next-Token-Failures are comparing it to the libraries listed below
Sorting:
- Directional Preference Alignment☆58Updated last year
- Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision☆124Updated last year
- The code for creating the iGSM datasets in papers "Physics of Language Models Part 2.1, Grade-School Math and the Hidden Reasoning Proces…☆80Updated 10 months ago
- ICML 2024 - Official Repository for EXO: Towards Efficient Exact Optimization of Language Model Alignment☆57Updated last year
- Code for "Reasoning to Learn from Latent Thoughts"☆122Updated 8 months ago
- Language models scale reliably with over-training and on downstream tasks☆100Updated last year
- Official github repo for the paper "Compression Represents Intelligence Linearly" [COLM 2024]☆143Updated last year
- ☆109Updated last year
- Code for ICLR 2025 Paper "What is Wrong with Perplexity for Long-context Language Modeling?"☆105Updated last month
- A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models☆68Updated 9 months ago
- [ICLR 2025] Code for the paper "Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planning"☆85Updated 9 months ago
- Online Adaptation of Language Models with a Memory of Amortized Contexts (NeurIPS 2024)☆70Updated last year
- [NeurIPS'24 Spotlight] Observational Scaling Laws☆59Updated last year
- Self-Supervised Alignment with Mutual Information☆21Updated last year
- Official implementation of Bootstrapping Language Models via DPO Implicit Rewards☆44Updated 7 months ago
- Code for NeurIPS 2024 Spotlight: "Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations"☆85Updated last year
- A curated list of awesome resources dedicated to Scaling Laws for LLMs☆80Updated 2 years ago
- official implementation of ICLR'2025 paper: Rethinking Bradley-Terry Models in Preference-based Reward Modeling: Foundations, Theory, and…☆69Updated 8 months ago
- Replicating O1 inference-time scaling laws☆90Updated last year
- Official repository of paper "RNNs Are Not Transformers (Yet): The Key Bottleneck on In-context Retrieval"☆27Updated last year
- Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging☆111Updated 2 years ago
- Exploration of automated dataset selection approaches at large scales.☆50Updated 9 months ago
- [NeurIPS 2024 Spotlight] Code and data for the paper "Finding Transformer Circuits with Edge Pruning".☆62Updated 3 months ago
- Learning from preferences is a common paradigm for fine-tuning language models. Yet, many algorithmic design decisions come into play. Ou…☆32Updated last year
- ☆33Updated last year
- ☆51Updated last year
- ☆103Updated last year
- ☆100Updated last year
- Long Context Extension and Generalization in LLMs☆62Updated last year
- Code accompanying the paper "Noise Contrastive Alignment of Language Models with Explicit Rewards" (NeurIPS 2024)☆57Updated last year