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CombLM: Adapting Black-Box Language Models through Small Fine-Tuned
  Models

CombLM: Adapting Black-Box Language Models through Small Fine-Tuned Models

23 May 2023
Aitor Ormazabal
Mikel Artetxe
Eneko Agirre
ArXivPDFHTML

Papers citing "CombLM: Adapting Black-Box Language Models through Small Fine-Tuned Models"

5 / 5 papers shown
Title
Cross-Tokenizer Distillation via Approximate Likelihood Matching
Cross-Tokenizer Distillation via Approximate Likelihood Matching
Benjamin Minixhofer
Ivan Vulić
E. Ponti
59
0
0
25 Mar 2025
PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
Rana Muhammad Shahroz Khan
Pingzhi Li
Sukwon Yun
Zhenyu Wang
S. Nirjon
Chau-Wai Wong
Tianlong Chen
KELM
32
2
0
08 Oct 2024
Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in
  the Era of Large Language Models
Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models
Jinliang Lu
Ziliang Pang
Min Xiao
Yaochen Zhu
Rui Xia
Jiajun Zhang
MoMe
27
17
0
08 Jul 2024
HYDRA: Model Factorization Framework for Black-Box LLM Personalization
HYDRA: Model Factorization Framework for Black-Box LLM Personalization
Yuchen Zhuang
Haotian Sun
Yue Yu
Rushi Qiang
Qifan Wang
Chao Zhang
Bo Dai
AAML
31
14
0
05 Jun 2024
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
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
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