This research presents Hydragen, a hardware-aware model that improves the efficiency of transformer-based large language models (LLMs) working with shared prefixes. It is common for LLMs to perform inferences on…
Continue readingThis research paper focuses on the identification of political actors who make claims in public debates, an important aspect in constructing discourse networks. It compares a traditional pipeline of dedicated…
Continue readingThe paper introduces a new method for text generation termed as non-exchangeable conformal nucleus sampling. This method is a novel extension of the conformal prediction framework, which is used for…
Continue readingThis article presents MAMI, a method to improve long sequence neuron captioning. Neuron labeling is a way to visualize how neurons in a deep neural network respond to certain patterns….
Continue readingThe article presents a research on evaluating the quality and variability of text generated by Large Language Models (LLMs). Conventional evaluation methods often fail to capture the holistic semantic equivalence,…
Continue readingThe study focuses on the development of Critique LLM, a new critique generation model. It addresses the need for comprehensive evaluation of Large Language Models (LLMs) like GPT-4 which are…
Continue readingThe article titled ‘All Should Be Equal in the Eyes of Language Models: Counterfactually Aware Fair Text Generation’, discusses the issue of biases in Language Models (LMs) and introduces a…
Continue readingThe article proposes a novel method, BRANCH-SOLVE-MERGE (BSM), to enhance the performance of Large Language Models (LLMs) in handling intricate language tasks. BSM comprises three modules – ‘branch’, ‘solve’, and…
Continue readingThis article focuses on the problem of factually incorrect responses generated by Language Models (LMs). The proposed solution involves augmenting LMs with knowledge retrieved from an external source. However, this…
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