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Scaling up Discovery of Latent Concepts in Deep NLP Models

Scaling up Discovery of Latent Concepts in Deep NLP Models

20 August 2023
Majd Hawasly
Fahim Dalvi
Nadir Durrani
ArXivPDFHTML

Papers citing "Scaling up Discovery of Latent Concepts in Deep NLP Models"

7 / 7 papers shown
Title
Latent Concept-based Explanation of NLP Models
Latent Concept-based Explanation of NLP Models
Xuemin Yu
Fahim Dalvi
Nadir Durrani
Marzia Nouri
Hassan Sajjad
LRM
FAtt
19
1
0
18 Apr 2024
Can LLMs facilitate interpretation of pre-trained language models?
Can LLMs facilitate interpretation of pre-trained language models?
Basel Mousi
Nadir Durrani
Fahim Dalvi
28
12
0
22 May 2023
Beyond Prompting: Making Pre-trained Language Models Better Zero-shot
  Learners by Clustering Representations
Beyond Prompting: Making Pre-trained Language Models Better Zero-shot Learners by Clustering Representations
Yu Fei
Ping Nie
Zhao Meng
Roger Wattenhofer
Mrinmaya Sachan
VLM
35
20
0
29 Oct 2022
On the Transformation of Latent Space in Fine-Tuned NLP Models
On the Transformation of Latent Space in Fine-Tuned NLP Models
Nadir Durrani
Hassan Sajjad
Fahim Dalvi
Firoj Alam
27
17
0
23 Oct 2022
Topic Modeling with Contextualized Word Representation Clusters
Topic Modeling with Contextualized Word Representation Clusters
Laure Thompson
David M. Mimno
88
82
0
23 Oct 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
294
6,927
0
20 Apr 2018
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
29,632
0
16 Jan 2013
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