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---
title: Optillm
emoji: 💬
colorFrom: yellow
colorTo: purple
sdk: gradio
sdk_version: 4.36.1
app_file: app.py
pinned: false
license: apache-2.0
---
## References
- [Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation](https://arxiv.org/abs/2409.12941)
- [Writing in the Margins: Better Inference Pattern for Long Context Retrieval](https://www.arxiv.org/abs/2408.14906)
- [Chain-of-Thought Reasoning Without Prompting](https://arxiv.org/abs/2402.10200)
- [Re-Reading Improves Reasoning in Large Language Models](https://arxiv.org/abs/2309.06275)
- [In-Context Principle Learning from Mistakes](https://arxiv.org/abs/2402.05403)
- [Planning In Natural Language Improves LLM Search For Code Generation](https://arxiv.org/abs/2409.03733)
- [Self-Consistency Improves Chain of Thought Reasoning in Language Models](https://arxiv.org/abs/2203.11171)
- [Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers](https://arxiv.org/abs/2408.06195)
- [Mixture-of-Agents Enhances Large Language Model Capabilities](https://arxiv.org/abs/2406.04692)
- [Prover-Verifier Games improve legibility of LLM outputs](https://arxiv.org/abs/2407.13692)
- [Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning](https://arxiv.org/abs/2405.00451)
- [Unsupervised Evaluation of Code LLMs with Round-Trip Correctness](https://arxiv.org/abs/2402.08699)
- [Patched MOA: optimizing inference for diverse software development tasks](https://arxiv.org/abs/2407.18521)
- [Patched RTC: evaluating LLMs for diverse software development tasks](https://arxiv.org/abs/2407.16557)