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Found 6 papers, 1 papers with code
Impact of Preference Noise on the Alignment Performance of Generative Language Models
A key requirement in developing Generative Language Models (GLMs) is to have their values aligned with human values.
Best-of-Venom: Attacking RLHF by Injecting Poisoned Preference Data
Reinforcement Learning from Human Feedback (RLHF) is a popular method for aligning Language Models (LM) with human values and preferences.
DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback
Then, it uses two VLMs to select the best generation: a Visual Question Answering model that measures the alignment of generated images to the text, and another that measures the generation's aesthetic quality.
PaRaDe: Passage Ranking using Demonstrations with Large Language Models
Recent studies show that large language models (LLMs) can be instructed to effectively perform zero-shot passage re-ranking, in which the results of a first stage retrieval method, such as BM25, are rated and reordered to improve relevance.
OpenMSD: Towards Multilingual Scientific Documents Similarity Measurement
We propose the first multilingual scientific documents dataset, Open-access Multilingual Scientific Documents (OpenMSD), which has 74M papers in 103 languages and 778M citation pairs.
LayerNAS: Neural Architecture Search in Polynomial Complexity
For a model architecture with $L$ layers, we perform layerwise-search for each layer, selecting from a set of search options $\mathbb{S}$.
