Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens

7 May 2023

Papers citing "Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens"

7 / 7 papers shown

Title
KV-Distill: Nearly Lossless Learnable Context Compression for LLMs Vivek Chari Guanghui Qin Benjamin Van Durme VLM 61 0 0 13 Mar 2025
Evidence-Enhanced Triplet Generation Framework for Hallucination Alleviation in Generative Question Answering Haowei Du Huishuai Zhang Dongyan Zhao HILM 14 0 0 27 Aug 2024
LLaVolta: Efficient Multi-modal Models via Stage-wise Visual Context Compression Jieneng Chen Luoxin Ye Ju He Zhao-Yang Wang Daniel Khashabi Alan Yuille VLM 27 5 0 28 Jun 2024
Dodo: Dynamic Contextual Compression for Decoder-only LMs Guanghui Qin Corby Rosset Ethan C. Chau Nikhil Rao Benjamin Van Durme 11 7 0 03 Oct 2023
ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts Yuta Koreeda Christopher D. Manning AILaw 87 96 0 05 Oct 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe ... Horace He Anish Thite Noa Nabeshima Shawn Presser Connor Leahy AIMat 245 1,977 0 31 Dec 2020
Big Bird: Transformers for Longer Sequences Manzil Zaheer Guru Guruganesh Kumar Avinava Dubey Joshua Ainslie Chris Alberti ... Philip Pham Anirudh Ravula Qifan Wang Li Yang Amr Ahmed VLM 249 1,982 0 28 Jul 2020