[2] Self-Rewarding Language Models: arxiv.org/abs/2401.1002 [3] Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment: arxiv.org/abs/2401.1247 [4] Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena: arxiv.org/abs/2306.0568发布...
Train Models Most hyper parameters are the same as except for the number of steps (the original Humback trains 1600 steps on 512k samples). # change the `--data_path`in`scripts/train_seed.sh` $ bash scripts/train_seed.sh 参考链接: https://github.com/yizhongw/self-instructhttps://pape...
Abstract: Instruction tuning is a supervised fine-tuning approach that significantly improves the ability of large language models (LLMs) to follow human instructions. We propose SelfCodeAlign, the first fully transparent and permissive pipeline for self-aligning code LLMs without extensive human annota...
Considerable efforts have been invested in augmenting the role-playing proficiency of open-source large language models (LLMs) by emulating proprietary counterparts. Nevertheless, we posit that LLMs inherently harbor role-play capabilities, owing to the extensive knowledge of characters and potential dial...
University of California, Berkeley New York University ABSTRACT Large Language Models (LLMs) are rapidly surpassing human knowledge in many domains. While improving these models traditionally relies on costly human data, recent self-rewarding mechanisms (Yuan et al., 2024) have shown that LLMs can...
[3] Self-Rewarding Language Models [4] huggingface.co/snorkela [5] LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion [6] Noise Contrastive Alignment of Language Models with Explicit Rewards 小广告 #Self-Play Preference Optimization for Language Model Alignment...
This is the official repo for our EMNLP (Main) 2024 paper: Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models, a novel tuning-free inference-time algorithm to self-align large language models (LLMs) with human preference. Why tuning-free self-alignme...
Introduction Large parts machining is performed on a near-to-shape raw part, obtained by processes like casting or welding. These raw parts very often do not have any reliable surface or feature reference that can be used for in-machine alignment. However, initial alignment of the part at ...
However, as proved by Zhang in [37], these FIR filters should be designed with very large orders to meet the de-nosing requirement, thus resulting in the increasing of both the computation burden and alignment time. In [39], we adopt the infinite impulse response (IIR) digital low-pass ...
"Our self-training approach assumes access to a base language model, a small amount of seed data, and a collection of unlabelled examples, e.g. a web corpus. The unlabelled data is a large, diverse set of human-written documents which includes writing about all manner of topics humans are...