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On the Importance of Data Size in Probing Fine-tuned Models

On the Importance of Data Size in Probing Fine-tuned Models

17 March 2022
Houman Mehrafarin
S. Rajaee
Mohammad Taher Pilehvar
ArXivPDFHTML

Papers citing "On the Importance of Data Size in Probing Fine-tuned Models"

6 / 6 papers shown
Title
Pixology: Probing the Linguistic and Visual Capabilities of Pixel-based
  Language Models
Pixology: Probing the Linguistic and Visual Capabilities of Pixel-based Language Models
Kushal Tatariya
Vladimir Araujo
Thomas Bauwens
Miryam de Lhoneux
VLM
33
0
0
15 Oct 2024
The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions
The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions
Stefan Sylvius Wagner
Maike Behrendt
Marc Ziegele
Stefan Harmeling
32
9
0
18 Jun 2024
Designing with Language: Wireframing UI Design Intent with Generative
  Large Language Models
Designing with Language: Wireframing UI Design Intent with Generative Large Language Models
Sidong Feng
Mingyue Yuan
Jieshan Chen
Zhenchang Xing
Chunyang Chen
AI4CE
3DV
19
7
0
12 Dec 2023
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
29
18
0
23 Oct 2022
Spying on your neighbors: Fine-grained probing of contextual embeddings
  for information about surrounding words
Spying on your neighbors: Fine-grained probing of contextual embeddings for information about surrounding words
Josef Klafka
Allyson Ettinger
43
42
0
04 May 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
297
6,950
0
20 Apr 2018
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