SILG: The Multi-domain Symbolic Interactive Language Grounding Benchmark

By Victor Zhong, Austin W. Hanjie, Sida I. Wang, Karthik Narasimhan, Luke S. Zettlemoyer. 2021

23 citations recorded by the source corpus.

Subfields: Natural Language Processing, Multimodal Learning

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Shunyu Yao
2. Karthik Narasimhan
3. Theodore R. Sumers
4. John Yang
5. Howard Chen
6. Thomas L. Griffiths
7. Matthew J. Hausknecht
8. Prithviraj Ammanabrolu

In Multimodal Learning

1. Karthik Narasimhan
2. Theodore R. Sumers

Citations in the corpus

• WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents (2022, background): “Recent advances in natural language processing (NLP) and reinforcement learning (RL) have brought about several exciting developments in agents that can perform sequential decision making while making use of linguistic context [30, 50, 58].”
• Cognitive Architectures for Language Agents (2023, background): “In RL, “reading to learn” approaches (Branavan et al., 2012; Narasimhan et al., 2018; Hanjie et al., 2021; Zhong et al., 2021) leverage game manuals and facts as a semantic memory to affect the policy.”