---
license: mit
task_categories:
- text-classification
tags:
- AI
- ICLR
- ICLR2023
---
## ICLR 2023 International Conference on Learning Representations 2023 Accepted Paper Meta Info Dataset

This dataset is collect from the ICLR 2023 OpenReview website (https://openreview.net/group?id=ICLR.cc/2023/Conference#tab-accept-oral) as well as the arxiv website DeepNLP paper arxiv (http://www.deepnlp.org/content/paper/iclr2023). For researchers who are interested in doing analysis of ICLR 2023 accepted papers and potential trends, you can use the already cleaned up json files. 
Each row contains the meta information of a paper in the ICLR 2023 conference. To explore more AI & Robotic papers (NIPS/ICML/ICLR/IROS/ICRA/etc) and AI equations, feel free to navigate the Equation Search Engine (http://www.deepnlp.org/search/equation) as well as the AI Agent Search Engine to find the deployed AI Apps and Agents (http://www.deepnlp.org/search/agent) in your domain. 


### Meta Information of Json File

```
{
    "title": "Encoding Recurrence into Transformers",
    "url": "https://openreview.net/forum?id=7YfHla7IxBJ",
    "detail_url": "https://openreview.net/forum?id=7YfHla7IxBJ",
    "authors": "Feiqing Huang,Kexin Lu,Yuxi CAI,Zhen Qin,Yanwen Fang,Guangjian Tian,Guodong Li",
    "tags": "ICLR 2023,Top 5%",
    "abstract": "This paper novelly breaks down with ignorable loss an RNN layer into a sequence of simple RNNs, each of which can be further rewritten into a lightweight positional encoding matrix of a self-attention, named the Recurrence Encoding Matrix (REM). Thus, recurrent dynamics introduced by the RNN layer can be encapsulated into the positional encodings of a multihead self-attention, and this makes it possible to seamlessly incorporate these recurrent dynamics into a Transformer, leading to a new module, Self-Attention with Recurrence (RSA). The proposed module can leverage the recurrent inductive bias of REMs to achieve a better sample efficiency than its corresponding baseline Transformer, while the self-attention is used to model the remaining non-recurrent signals. The relative proportions of these two components are controlled by a data-driven gated mechanism, and the effectiveness of RSA modules are demonstrated by four sequential learning tasks.",
    "pdf": "https://openreview.net/pdf/70636775789b51f219cb29634cc7c794cc86577b.pdf"
}

```



## Related

## AI Equation
[List of AI Equations and Latex](http://www.deepnlp.org/equation/category/ai) <br>
[List of Math Equations and Latex](http://www.deepnlp.org/equation/category/math) <br>
[List of Physics Equations and Latex](http://www.deepnlp.org/equation/category/physics) <br>
[List of Statistics Equations and Latex](http://www.deepnlp.org/equation/category/statistics) <br>
[List of Machine Learning Equations and Latex](http://www.deepnlp.org/equation/category/machine%20learning) <br>

## AI Agent Marketplace and Search
[AI Agent Marketplace and Search](http://www.deepnlp.org/search/agent) <br>
[Robot Search](http://www.deepnlp.org/search/robot) <br>
[Equation and Academic search](http://www.deepnlp.org/search/equation) <br>
[AI & Robot Comprehensive Search](http://www.deepnlp.org/search) <br>
[AI & Robot Question](http://www.deepnlp.org/question) <br>
[AI & Robot Community](http://www.deepnlp.org/community) <br>
[AI Agent Marketplace Blog](http://www.deepnlp.org/blog/ai-agent-marketplace-and-search-portal-reviews-2025) <br>

## AI Agent Reviews
[AI Agent Marketplace Directory](http://www.deepnlp.org/store/ai-agent) <br>
[Microsoft AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-microsoft-ai-agent) <br>
[Claude AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-claude-ai-agent) <br>
[OpenAI AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-openai-ai-agent) <br>
[Saleforce AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-salesforce-ai-agent) <br>
[AI Agent Builder Reviews](http://www.deepnlp.org/store/ai-agent/ai-agent-builder) <br>