31 citations · 46 across the 15 of their papers we have counts for
4 papers · 1 filter
Exploring Demonstration Ensembling for In-context Learning
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee +2
In-context learning (ICL) operates by showing language models (LMs) examples of input-output pairs for a given task, i.e., demonstrations. The standard approach for ICL is to promp…
BOLT: Fast Energy-based Controlled Text Generation with Tunable Biases
Xin Liu, Muhammad Khalifa, Lu Wang
Energy-based models (EBMs) have gained popularity for controlled text generation due to their high applicability to a wide range of constraints. However, sampling from EBMs is non-…
GRACE: Discriminator-Guided Chain-of-Thought Reasoning
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee +2
In the context of multi-step reasoning, e.g., with chain-of-thought, language models (LMs) can easily assign a high likelihood to incorrect steps. As a result, decoding strategies…
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
Oana Ignat, Zhijing Jin, Artem Abzaliev +19
Recent progress in large language models (LLMs) has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse t…