gregorbachmann / Next-Token-FailuresLinks
☆108Updated 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:
- [ICLR 2025] Code for the paper "Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planning"☆86Updated 11 months ago
- Language models scale reliably with over-training and on downstream tasks☆99Updated last year
- ICML 2024 - Official Repository for EXO: Towards Efficient Exact Optimization of Language Model Alignment☆57Updated last year
- Directional Preference Alignment☆58Updated last year
- Code for "Reasoning to Learn from Latent Thoughts"☆124Updated 10 months ago
- Official github repo for the paper "Compression Represents Intelligence Linearly" [COLM 2024]☆147Updated last year
- Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision☆124Updated last year
- Code for ICLR 2025 Paper "What is Wrong with Perplexity for Long-context Language Modeling?"☆110Updated 3 months ago
- A curated list of awesome resources dedicated to Scaling Laws for LLMs☆81Updated 2 years ago
- Official repository of paper "RNNs Are Not Transformers (Yet): The Key Bottleneck on In-context Retrieval"☆27Updated last year
- Code for NeurIPS 2024 Spotlight: "Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations"☆88Updated last year
- Long Context Extension and Generalization in LLMs☆62Updated 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…☆84Updated last year
- Online Adaptation of Language Models with a Memory of Amortized Contexts (NeurIPS 2024)☆73Updated last year
- Sparse Backpropagation for Mixture-of-Expert Training☆29Updated last year
- [NeurIPS-2024] 📈 Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies https://arxiv.org/abs/2407.13623☆89Updated last year
- Official implementation of Bootstrapping Language Models via DPO Implicit Rewards☆47Updated 9 months ago
- [NeurIPS 2024 Spotlight] Code and data for the paper "Finding Transformer Circuits with Edge Pruning".☆64Updated 5 months ago
- A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models☆71Updated 11 months ago
- ☆57Updated last year
- Stick-breaking attention☆62Updated 7 months ago
- Code for paper "Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning"☆84Updated 2 years ago
- This is code for most of the experiments in the paper Understanding the Effects of RLHF on LLM Generalisation and Diversity☆47Updated 2 years ago
- ☆112Updated last year
- Code accompanying the paper "Noise Contrastive Alignment of Language Models with Explicit Rewards" (NeurIPS 2024)☆58Updated last year
- official implementation of ICLR'2025 paper: Rethinking Bradley-Terry Models in Preference-based Reward Modeling: Foundations, Theory, and…☆70Updated 10 months ago
- ☆45Updated 2 years ago
- Simple and efficient pytorch-native transformer training and inference (batched)☆79Updated last year
- Reinforcing General Reasoning without Verifiers☆93Updated 7 months ago
- [NeurIPS'24 Spotlight] Observational Scaling Laws☆58Updated last year