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CoLLEGe: Concept Embedding Generation for Large Language Models

CoLLEGe: Concept Embedding Generation for Large Language Models

22 March 2024
Ryan Teehan
Brenden Lake
Mengye Ren
ArXivPDFHTML

Papers citing "CoLLEGe: Concept Embedding Generation for Large Language Models"

5 / 5 papers shown
Title
VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction
VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction
N. Wang
Bingkun Yao
Jie Zhou
Yuchen Hu
Xi Wang
Nan Guan
Zhe Jiang
31
0
0
27 Apr 2025
Meta-learning via Language Model In-context Tuning
Meta-learning via Language Model In-context Tuning
Yanda Chen
Ruiqi Zhong
Sheng Zha
George Karypis
He He
218
155
0
15 Oct 2021
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
ReadOnce Transformers: Reusable Representations of Text for Transformers
ReadOnce Transformers: Reusable Representations of Text for Transformers
Shih-Ting Lin
Ashish Sabharwal
Tushar Khot
27
3
0
24 Oct 2020
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
228
31,150
0
16 Jan 2013
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