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Exploring the Reasoning Abilities of Multimodal Large Language Models
  (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning

Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning

10 January 2024
Yiqi Wang
Wentao Chen
Xiaotian Han
Xudong Lin
Haiteng Zhao
Yongfei Liu
Bohan Zhai
Jianbo Yuan
Quanzeng You
Hongxia Yang
    LRM
ArXivPDFHTML

Papers citing "Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning"

11 / 61 papers shown
Title
Complexity-Based Prompting for Multi-Step Reasoning
Complexity-Based Prompting for Multi-Step Reasoning
Yao Fu
Hao-Chun Peng
Ashish Sabharwal
Peter Clark
Tushar Khot
ReLM
LRM
152
298
0
03 Oct 2022
Learn to Explain: Multimodal Reasoning via Thought Chains for Science
  Question Answering
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
Pan Lu
Swaroop Mishra
Tony Xia
Liang Qiu
Kai-Wei Chang
Song-Chun Zhu
Oyvind Tafjord
Peter Clark
A. Kalyan
ELM
ReLM
LRM
198
1,089
0
20 Sep 2022
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language,
  Vision, and Action
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action
Dhruv Shah
B. Osinski
Brian Ichter
Sergey Levine
LM&Ro
136
430
0
10 Jul 2022
Large Language Models are Zero-Shot Reasoners
Large Language Models are Zero-Shot Reasoners
Takeshi Kojima
S. Gu
Machel Reid
Yutaka Matsuo
Yusuke Iwasawa
ReLM
LRM
291
2,712
0
24 May 2022
On the Paradox of Learning to Reason from Data
On the Paradox of Learning to Reason from Data
Honghua Zhang
Liunian Harold Li
Tao Meng
Kai-Wei Chang
Guy Van den Broeck
NAI
ReLM
OOD
LRM
132
102
0
23 May 2022
Language Models with Image Descriptors are Strong Few-Shot
  Video-Language Learners
Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners
Zhenhailong Wang
Manling Li
Ruochen Xu
Luowei Zhou
Jie Lei
...
Chenguang Zhu
Derek Hoiem
Shih-Fu Chang
Mohit Bansal
Heng Ji
MLLM
VLM
162
134
0
22 May 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
OSLM
ALM
301
11,730
0
04 Mar 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason W. Wei
Xuezhi Wang
Dale Schuurmans
Maarten Bosma
Brian Ichter
F. Xia
Ed H. Chi
Quoc Le
Denny Zhou
LM&Ro
LRM
AI4CE
ReLM
315
8,261
0
28 Jan 2022
Fantastically Ordered Prompts and Where to Find Them: Overcoming
  Few-Shot Prompt Order Sensitivity
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
Yao Lu
Max Bartolo
Alastair Moore
Sebastian Riedel
Pontus Stenetorp
AILaw
LRM
274
882
0
18 Apr 2021
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize
  Long-Tail Visual Concepts
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
Soravit Changpinyo
P. Sharma
Nan Ding
Radu Soricut
VLM
273
845
0
17 Feb 2021
What Makes Good In-Context Examples for GPT-$3$?
What Makes Good In-Context Examples for GPT-333?
Jiachang Liu
Dinghan Shen
Yizhe Zhang
Bill Dolan
Lawrence Carin
Weizhu Chen
AAML
RALM
275
1,296
0
17 Jan 2021
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