Summary of Improving Autoregressive Training with Dynamic Oracles, by Jianing Yang et al.
Improving Autoregressive Training with Dynamic Oraclesby Jianing Yang, Harshine Visvanathan, Yilin Wang, Xinyi Hu, Matthew…
Improving Autoregressive Training with Dynamic Oraclesby Jianing Yang, Harshine Visvanathan, Yilin Wang, Xinyi Hu, Matthew…
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Verificationby Yunzhen Feng, Elvis Dohmatob, Pu…
CERET: Cost-Effective Extrinsic Refinement for Text Generationby Jason Cai, Hang Su, Monica Sunkara, Igor Shalyminov,…
SUMIE: A Synthetic Benchmark for Incremental Entity Summarizationby Eunjeong Hwang, Yichao Zhou, Beliz Gunel, James…
Which Side Are You On? A Multi-task Dataset for End-to-End Argument Summarisation and Evaluationby Hao…
Exploring Robustness in Doctor-Patient Conversation Summarization: An Analysis of Out-of-Domain SOAP Notesby Yu-Wen Chen, Julia…
Shotluck Holmes: A Family of Efficient Small-Scale Large Language Vision Models For Video Captioning and…
Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Modelsby Zhanhui Zhou, Zhixuan…
Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inferenceby Hao Mark Chen, Wayne Luk,…
Exploiting LLM Quantizationby Kazuki Egashira, Mark Vero, Robin Staab, Jingxuan He, Martin VechevFirst submitted to…