NLP Interests

Feb 12, 2023|Apr 18, 2023
Eren Chenyang Zhao 赵晨阳
Eren Chenyang Zhao 赵晨阳
type
Page
status
Published
date
Feb 12, 2023
slug
NLP
summary
NLP Brain-Storming
tags
2023 Spring
category
Research
icon
password

NLP

Bidirectional Language Models Are Also Few-shot Learners
Large language models such as GPT-3 (Brown et al., 2020) can perform arbitrary tasks without undergoing fine-tuning after being prompted with only a few labeled examples. An arbitrary task can be...
Bidirectional Language Models Are Also Few-shot Learners
https://arxiv.org/abs/2209.14500
Bidirectional Language Models Are Also Few-shot Learners
Understanding Large Language Models -- A Transformative Reading List
Since transformers have such a big impact on everyone's research agenda, I wanted to flesh out a short reading list for machine learning researchers and prac...
Understanding Large Language Models -- A Transformative Reading List
https://sebastianraschka.com/blog/2023/llm-reading-list.html
Understanding Large Language Models -- A Transformative Reading List
Exploring the Benefits of Training Expert Language Models over...
Recently, Language Models (LMs) instruction-tuned on multiple tasks, also known as multitask-prompted fine-tuning (MT), have shown the capability to generalize to unseen tasks. Previous work has...
Exploring the Benefits of Training Expert Language Models over...
https://arxiv.org/abs/2302.03202
Exploring the Benefits of Training Expert Language Models over...
Reasoning with Language Model Prompting: A Survey
Reasoning, as an essential ability for complex problem-solving, can provide back-end support for various real-world applications, such as medical diagnosis, negotiation, etc. This paper provides a...
Reasoning with Language Model Prompting: A Survey
https://arxiv.org/abs/2212.09597
Reasoning with Language Model Prompting: A Survey
Prompt4ReasoningPapers
zjunlp • Updated Oct 4, 2025
​​What learning algorithm is in-context learning? Investigations...
Keywords: in-context learning, transformers, sequence models, deep learning, meta learning TL;DR: We prove that the transformers can implement learning algorithms for linear models based e.g gradient descent, then observe they closely match the predictors of known algorithms, transitioning between different predictors as transformer depth vary.
​​What learning algorithm is in-context learning? Investigations...
https://openreview.net/forum?id=0g0X4H8yN4I
​​What learning algorithm is in-context learning? Investigations...
openreview.net
https://openreview.net/pdf?id=0g0X4H8yN4I
In-context Learning and Induction Heads
In-context Learning and Induction Heads
https://transformer-circuits.pub/2022/in-context-learning-and-induction-heads/index.html
 
GitHub - lupantech/dl4math: Resources of deep learning for mathematical reasoning (DL4MATH).
Resources of deep learning for mathematical reasoning (DL4MATH). - GitHub - lupantech/dl4math: Resources of deep learning for mathematical reasoning (DL4MATH).
GitHub - lupantech/dl4math: Resources of deep learning for mathematical reasoning (DL4MATH).
https://github.com/lupantech/dl4math
GitHub - lupantech/dl4math: Resources of deep learning for mathematical reasoning (DL4MATH).
A Survey of Deep Learning for Mathematical Reasoning
Mathematical reasoning is a fundamental aspect of human intelligence and is applicable in various fields, including science, engineering, finance, and everyday life. The development of artificial...
A Survey of Deep Learning for Mathematical Reasoning
https://arxiv.org/abs/2212.10535
A Survey of Deep Learning for Mathematical Reasoning
 
Home - AI Paper Collector
Home - AI Paper Collector
https://ai-paper-collector.vercel.app/
 
GPTScore: Evaluate as You Desire
Generative Artificial Intelligence (AI) has enabled the development of sophisticated models that are capable of producing high-caliber text, images, and other outputs through the utilization of...
GPTScore: Evaluate as You Desire
https://arxiv.org/abs/2302.04166
GPTScore: Evaluate as You Desire
Larger language models do in-context learning differently
We study how in-context learning (ICL) in language models is affected by semantic priors versus input-label mappings. We investigate two setups-ICL with flipped labels and ICL with...
Larger language models do in-context learning differently
https://arxiv.org/abs/2303.03846
Larger language models do in-context learning differently
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
BIG-Bench (Srivastava et al., 2022) is a diverse evaluation suite that focuses on tasks believed to be beyond the capabilities of current language models. Language models have already made good...
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
https://arxiv.org/abs/2210.09261
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
 
 
The Web Is Your Oyster - Knowledge-Intensive NLP against a Very...
In order to address increasing demands of real-world applications, the research for knowledge-intensive NLP (KI-NLP) should advance by capturing the challenges of a truly open-domain environment:...
The Web Is Your Oyster - Knowledge-Intensive NLP against a Very...
https://arxiv.org/abs/2112.09924
The Web Is Your Oyster - Knowledge-Intensive NLP against a Very...
 
Dense Text Retrieval based on Pretrained Language Models: A Survey
Text retrieval is a long-standing research topic on information seeking, where a system is required to return relevant information resources to user's queries in natural language. From classic...
Dense Text Retrieval based on Pretrained Language Models: A Survey
https://arxiv.org/abs/2211.14876
Dense Text Retrieval based on Pretrained Language Models: A Survey
 
Generate rather than Retrieve: Large Language Models are Strong...
Knowledge-intensive tasks, such as open-domain question answering (QA), require access to a large amount of world or domain knowledge. A common approach for knowledge-intensive tasks is to employ...
Generate rather than Retrieve: Large Language Models are Strong...
https://arxiv.org/abs/2209.10063
Generate rather than Retrieve: Large Language Models are Strong...
 
arxiv.org
https://arxiv.org/pdf/2303.12712.pdf

PhD

www.cs.cmu.edu
http://www.cs.cmu.edu/~harchol/gradschooltalk.pdf
Martian Computing Research | 火星计算研究所
StormRaiser's (temporary) personal site
Martian Computing Research | 火星计算研究所
https://stormraiser.me/
Martian Computing Research | 火星计算研究所
 

Fancy

PromptPerfect - Elevate your prompts to perfection
Optimize prompts for GPT-4, ChatGPT, MidJourney, DALL-E, StableDiffusion and Lexica. Automatic prompt engineering done right!
PromptPerfect - Elevate your prompts to perfection
https://promptperfect.jina.ai/
PromptPerfect - Elevate your prompts to perfection
Research