ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2307.05052
  4. Cited By
Towards Understanding In-Context Learning with Contrastive
  Demonstrations and Saliency Maps
v1v2v3v4 (latest)

Towards Understanding In-Context Learning with Contrastive Demonstrations and Saliency Maps

11 July 2023
Fuxiao Liu
Paiheng Xu
Zongxi Li
Yue Feng
Hyemi Song
ArXiv (abs)PDFHTMLGithub (2★)

Papers citing "Towards Understanding In-Context Learning with Contrastive Demonstrations and Saliency Maps"

18 / 18 papers shown
Title
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction
Melkamu Mersha
Khang Lam
Joseph Wood
Ali AlShami
Jugal Kalita
XAIAI4TS
283
34
0
30 Aug 2024
Evaluating the Reliability of Self-Explanations in Large Language Models
Evaluating the Reliability of Self-Explanations in Large Language Models
Korbinian Randl
John Pavlopoulos
Aron Henriksson
Tony Lindgren
LRM
108
1
0
19 Jul 2024
In-Context Learning with Long-Context Models: An In-Depth Exploration
In-Context Learning with Long-Context Models: An In-Depth Exploration
Amanda Bertsch
Maor Ivgi
Uri Alon
Jonathan Berant
Matthew R. Gormley
Matthew R. Gormley
Graham Neubig
ReLMAIMat
179
80
0
30 Apr 2024
A Survey on Multimodal Large Language Models
A Survey on Multimodal Large Language Models
Shukang Yin
Chaoyou Fu
Sirui Zhao
Ke Li
Xing Sun
Tong Xu
Enhong Chen
MLLMLRM
133
607
0
23 Jun 2023
DocumentCLIP: Linking Figures and Main Body Text in Reflowed Documents
DocumentCLIP: Linking Figures and Main Body Text in Reflowed Documents
Fuxiao Liu
Hao Tan
Chris Tensmeyer
CLIPVLM
84
18
0
09 Jun 2023
Larger language models do in-context learning differently
Larger language models do in-context learning differently
Jerry W. Wei
Jason W. Wei
Yi Tay
Dustin Tran
Albert Webson
...
Xinyun Chen
Hanxiao Liu
Da Huang
Denny Zhou
Tengyu Ma
ReLMLRM
107
374
0
07 Mar 2023
What learning algorithm is in-context learning? Investigations with
  linear models
What learning algorithm is in-context learning? Investigations with linear models
Ekin Akyürek
Dale Schuurmans
Jacob Andreas
Tengyu Ma
Denny Zhou
102
493
0
28 Nov 2022
Complementary Explanations for Effective In-Context Learning
Complementary Explanations for Effective In-Context Learning
Xi Ye
Srini Iyer
Asli Celikyilmaz
Ves Stoyanov
Greg Durrett
Ramakanth Pasunuru
ReLMLRM
97
96
0
25 Nov 2022
PaLM: Scaling Language Modeling with Pathways
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery
Sharan Narang
Jacob Devlin
Maarten Bosma
Gaurav Mishra
...
Kathy Meier-Hellstern
Douglas Eck
J. Dean
Slav Petrov
Noah Fiedel
PILMLRM
529
6,293
0
05 Apr 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLMALM
886
13,207
0
04 Mar 2022
Rethinking the Role of Demonstrations: What Makes In-Context Learning
  Work?
Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
Sewon Min
Xinxi Lyu
Ari Holtzman
Mikel Artetxe
M. Lewis
Hannaneh Hajishirzi
Luke Zettlemoyer
LLMAGLRM
184
1,498
0
25 Feb 2022
An Explanation of In-context Learning as Implicit Bayesian Inference
An Explanation of In-context Learning as Implicit Bayesian Inference
Sang Michael Xie
Aditi Raghunathan
Percy Liang
Tengyu Ma
ReLMBDLVPVLMLRM
225
764
0
03 Nov 2021
Visual News: Benchmark and Challenges in News Image Captioning
Visual News: Benchmark and Challenges in News Image Captioning
Fuxiao Liu
Yinghan Wang
Tianlu Wang
Vicente Ordonez
VLM
69
116
0
08 Oct 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
889
42,463
0
28 May 2020
SmoothGrad: removing noise by adding noise
SmoothGrad: removing noise by adding noise
D. Smilkov
Nikhil Thorat
Been Kim
F. Viégas
Martin Wattenberg
FAttODL
210
2,236
0
12 Jun 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OODFAtt
193
6,024
0
04 Mar 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,071
0
16 Feb 2016
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
314
7,321
0
20 Dec 2013
1