1 citations · 1 across the 9 of their papers we have counts for
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Scaling Parameter-Constrained Language Models with Quality Data
Ernie Chang, Matteo Paltenghi, Yang Li +7
Scaling laws in language modeling traditionally quantify training loss as a function of dataset size and model parameters, providing compute-optimal estimates but often neglecting…
CoDi: Conversational Distillation for Grounded Question Answering
Patrick Huber, Arash Einolghozati, Rylan Conway +6
Distilling conversational skills into Small Language Models (SLMs) with approximately 1 billion parameters presents significant challenges. Firstly, SLMs have limited capacity in t…
Small But Funny: A Feedback-Driven Approach to Humor Distillation
Sahithya Ravi, Patrick Huber, Akshat Shrivastava +4
The emergence of Large Language Models (LLMs) has brought to light promising language generation capabilities, particularly in performing tasks like complex reasoning and creative…
Large Language Models as Zero-shot Dialogue State Tracker through Function Calling
Zekun Li, Zhiyu Zoey Chen, Mike Ross +7
Large language models (LLMs) are increasingly prevalent in conversational systems due to their advanced understanding and generative capabilities in general contexts. However, thei…