Instructions
Attention Is All You Need
Reviewer
admin (admin@AnthropLOGIC.onmicrosoft.com)
Chat History
<system> System.Conversation.Id = Knx9fjELUS8C30ejpwZP7c-us ; System.User.DisplayName = admin ; System.User.Email = admin@AnthropLOGIC.onmicrosoft.com
<assistant> Hello, I'm editoReview copilot, an AI assistant to peer review the AI interface of research articles and service plugins API.
**MODE A: research articles.**
Type these prompts in the 4-steps methodology (Step 3 is to be repeated):
1. _Start the review of a research article._
2. _Qualify as a reviewer of the research article._
3. _Decide whether the following fact is correct: This article introduces a groundbreaking algorithm for solving NP-hard optimization problems._
4. _Publish the editorial review of the researxh article._
**MODE B: service plugins API.**
Type these prompts in the 4-steps methodology (Step 3 is example of any actions):
1. _Start the review of a service plugin API._
2. _Search the business and services._
3. _Pay the product price of the service..._
4. _Publish the editorial review of the service plugin API._
_-----_
To restart, type:
_Restart the chat over._
<user> Start the review of a research article.
<assistant> Where is the title of the research article?
Type any title such as:
- _Attention Is All You Need_
- _Deep Learning for Symbolic Mathematics_
- _Tree-to-tree Neural Networks for Program Translation_
- _Introduction to inductive types_
- _..._
<user> Attention Is All You Need
<assistant> Where is the author's name of the research article?
Type any author name such as:
- _Ashish Vaswani_
- _Guillaume Lample, François Charton_
- _Xinyun Chen_
- _Camille Mary_
- _..._
<user> Ashish Vaswani
<assistant> Where is the shareable public URL address of the research article?
Type any URL such as:
- https://arxiv.org/pdf/1706.03762
- https://arxiv.org/pdf/2111.10968.pdf
- https://arxiv.org/pdf/1802.03691
- https://anthroplogic.sharepoint.com/:w:/s/cycle1/EYkAAiTctHlKm2pLCICagNcBawLjQWesCmefUk8Xi9CPxw?e=J0BZfI&action=embedview
- ...
<user> https://arxiv.org/pdf/1706.03762
<assistant> Where is the archive domain of the research article?
Type any archive domain such as:
- _arxiv.org_
- _hal.science_
- _osf.io_
- _com_
- _anthroplogic.sharepoint.com/sites/cycle1_
- _..._
<user> arxiv.org
<assistant> The research article "Attention Is All You Need" by Ashish Vaswani et al. proposes a new network architecture called the Transformer, which is based solely on attention mechanisms and eliminates the need for recurrent or convolutional neural networks. The article demonstrates that the Transformer model outperforms existing models in terms of translation quality, parallelizability, and training time. It achieves significant improvements in BLEU scores on machine translation tasks, such as the WMT 2014 English-to-German and English-to-French translation tasks. The authors also show that the Transformer model generalizes well to other tasks, including English constituency parsing. [1]
[1]: https://arxiv.org/abs/1706.03762 "[1706.03762] Attention Is All You Need"
<assistant> Step 2 is to Qualify as an editorial peer reviewer who can evaluate the research article paper.
<user> Qualify as a reviewer of the research article
<assistant> **Test to qualify the user as an editorial reviewer**
Some of the following statements are fake and not found in the research article. The qualification test is to choose only those statements which can be found within the research article by using a basic search query. Click on the corresponding button to discover the answer, then return to this message and repeat until you have chosen all those searchable statements
* The research article "Attention Is All You Need" proposes a new network architecture called the Transformer, which is based solely on attention mechanisms [REAL] .
* The authors of the research article achieved state-of-the-art results on machine translation tasks, surpassing existing models by a significant margin [REAL] .
* The Transformer model described in the research article achieved a BLEU score of 28.4 on the WMT 2014 English-to-German translation task [REAL] .
* The research article introduces a novel approach that combines recurrent and convolutional neural networks in an encoder-decoder configuration [FAKE].
* The authors of the research article conducted experiments on English constituency parsing and demonstrated that the Transformer model generalizes well to other tasks [REAL] .
<user> Decide whether the following fact is correct, in the context of the research article `Attention Is All You Need`, by the author Ashish Vaswani:
The research article "Attention Is All You Need" proposes a new network architecture called the Transformer, which is based solely on attention mechanisms [REAL] .
<assistant> <YES/> The statement is correct in the context of the research article "Attention Is All You Need" by Ashish Vaswani. The article indeed proposes a new network architecture called the Transformer, which is based solely on attention mechanisms [1].
[1]: https://arxiv.org/abs/1706.03762 "[1706.03762] Attention Is All You Need"
<user> Decide whether the following fact is correct, in the context of the research article `Attention Is All You Need`, by the author Ashish Vaswani:
The research article introduces a novel approach that combines recurrent and convolutional neural networks in an encoder-decoder configuration [FAKE].
<assistant> To clarify, did you mean:
<user> Decide whether a fact is correct
<assistant> <NO/> The fact's statement cannot be determined from the contents of the research article "Attention Is All You Need" by Ashish Vaswani [1].
[1]: https://arxiv.org/abs/1706.03762 "[1706.03762] Attention Is All You Need"
<user> Decide whether the following fact is correct, in the context of the research article `Attention Is All You Need`, by the author Ashish Vaswani:
The authors of the research article conducted experiments on English constituency parsing and demonstrated that the Transformer model generalizes well to other tasks [REAL] .
<assistant> <YES/>Yes, it is true that the authors of the research article conducted experiments on English constituency parsing and demonstrated that the Transformer model generalizes well to other tasks [1].
[1]: https://ar5iv.labs.arxiv.org/html/1706.03762v7 "[1706.03762] Attention Is All You Need"
<user> Publish the editorial review of the research article
<user> 798301
<assistant> **Publishing the editorial review.**
You are now signed-in as admin<admin@AnthropLOGIC.onmicrosoft.com >
Lastly append some further evaluation comments to this chat history, for publication to the auditable editoReview SharePoint back-end.. For example:
_My comments are that..._
<user> My comments are that this is a significant research article for language translation but also for rewriting theory....
<assistant> An error has occurred.
Error code: FlowActionBadRequest
Conversation Id: Knx9fjELUS8C30ejpwZP7c-us
Time (UTC): 2024-03-31T02:10:40.949Z.
<user> Restart the chat over.
<assistant> Are you sure you want to restart the conversation?
<user> Yes
<assistant> Hello, I'm editoReview copilot, an AI assistant to peer review the AI interface of research articles and service plugins API.
**MODE A: research articles.**
Type these prompts in the 4-steps methodology (Step 3 is to be repeated):
1. _Start the review of a research article._
2. _Qualify as a reviewer of the research article._
3. _Decide whether the following fact is correct: This article introduces a groundbreaking algorithm for solving NP-hard optimization problems._
4. _Publish the editorial review of the researxh article._
**MODE B: service plugins API.**
Type these prompts in the 4-steps methodology (Step 3 is example of any actions):
1. _Start the review of a service plugin API._
2. _Search the business and services._
3. _Pay the product price of the service..._
4. _Publish the editorial review of the service plugin API._
_-----_
To restart, type:
_Restart the chat over._
<user> Start the review of a research article.
<assistant> Where is the title of the research article?
Type any title such as:
- _Attention Is All You Need_
- _Deep Learning for Symbolic Mathematics_
- _Tree-to-tree Neural Networks for Program Translation_
- _Introduction to inductive types_
- _..._
<user> Attention Is All You Need
<assistant> Where is the author's name of the research article?
Type any author name such as:
- _Ashish Vaswani_
- _Guillaume Lample, François Charton_
- _Xinyun Chen_
- _Camille Mary_
- _..._
<user> Ashish Vaswani
<assistant> Where is the shareable public URL address of the research article?
Type any URL such as:
- https://arxiv.org/pdf/1706.03762
- https://arxiv.org/pdf/2111.10968.pdf
- https://arxiv.org/pdf/1802.03691
- https://anthroplogic.sharepoint.com/:w:/s/cycle1/EYkAAiTctHlKm2pLCICagNcBawLjQWesCmefUk8Xi9CPxw?e=J0BZfI&action=embedview
- ...
<user> https://arxiv.org/pdf/1706.03762
<assistant> Where is the archive domain of the research article?
Type any archive domain such as:
- _arxiv.org_
- _hal.science_
- _osf.io_
- _com_
- _anthroplogic.sharepoint.com/sites/cycle1_
- _..._
<user> arxiv.org
<assistant> The research article "Attention Is All You Need" by Ashish Vaswani et al. proposes a new network architecture called the Transformer, which is based solely on attention mechanisms and eliminates the need for recurrent or convolutional neural networks. The article demonstrates that the Transformer model outperforms existing models in terms of translation quality, parallelizability, and training time. It achieves significant improvements in BLEU scores on machine translation tasks, such as the WMT 2014 English-to-German and English-to-French translation tasks. The authors also show that the Transformer model generalizes well to other tasks, including English constituency parsing. [1]
[1]: https://arxiv.org/abs/1706.03762 "[1706.03762] Attention Is All You Need"
<assistant> Step 2 is to Qualify as an editorial peer reviewer who can evaluate the research article paper.
<user> Qualify as a reviewer of the research article
<assistant> **Test to qualify the user as an editorial reviewer**
Some of the following statements are fake and not found in the research article. The qualification test is to choose only those statements which can be found within the research article by using a basic search query. Click on the corresponding button to discover the answer, then return to this message and repeat until you have chosen all those searchable statements
* The research article "Attention Is All You Need" proposes a new network architecture called the Transformer, which is based solely on attention mechanisms [REAL] .
* The authors of the research article achieved state-of-the-art results on machine translation tasks, surpassing existing models by a significant margin [REAL] .
* The Transformer model described in the research article achieved a BLEU score of 28.4 on the WMT 2014 English-to-German translation task [REAL] .
* The research article introduces a novel approach that combines recurrent and convolutional neural networks in an encoder-decoder configuration [FAKE].
* The authors of the research article conducted experiments on English constituency parsing and demonstrated that the Transformer model generalizes well to other tasks [REAL] .
<user> Decide whether the following fact is correct, in the context of the research article `Attention Is All You Need`, by the author Ashish Vaswani:
The research article "Attention Is All You Need" proposes a new network architecture called the Transformer, which is based solely on attention mechanisms [REAL] .
Link to SharePoint Item: https://anthroplogic.sharepoint.com/sites/cycle1/_layouts/15/Doc.aspx?sourcedoc=%7B5211B9F8-FCA9-4337-9D91-62DDC7DA1506%7D&file=Attention%20Is%20All%20You%20Need.docx&action=default&mobileredirect=true