3 papers
cs.LG2024
A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs
Ankit Singh Rawat, Veeranjaneyulu Sadhanala, Afshin Rostamizadeh +12
A primary challenge in large language model (LLM) development is their onerous pre-training cost. Typically, such pre-training involves optimizing a self-supervised objective (such…
cs.CL2024
Faster Cascades via Speculative Decoding
Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat +4
Cascades and speculative decoding are two common approaches to improving language models' inference efficiency. Both approaches involve interleaving models of different sizes, but…
cs.CL2024
Analysis of Plan-based Retrieval for Grounded Text Generation
Ameya Godbole, Nicholas Monath, Seungyeon Kim +3
In text generation, hallucinations refer to the generation of seemingly coherent text that contradicts established knowledge. One compelling hypothesis is that hallucinations occur…