ACL 2022 Workshop LNLS Submissions

Revisiting the Roles of “Text” in Text Games
Yi Gu, Shunyu Yao, Chuang Gan, Joshua B. Tenenbaum, Mo Yu
- 28 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Unsupervised Cross-Task Generalization via Retrieval Augmentation
Bill Yuchen Lin, Kangmin Tan, Chris Scott Miller, Beiwen Tian, Xiang Ren
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Shared Autonomy for Robotic Manipulation with Language Corrections
Siddharth Karamcheti, Raj Palleti, Yuchen Cui, Percy Liang, Dorsa Sadigh
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Few-shot image classification by generating natural language rules
Wai Keen Vong, Brenden M. Lake
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
A survey on improving NLP models with human explanations
Mareike Hartmann, Daniel Sonntag
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
QuExEnt: Improved Zero-Shot Classification from Explanations Through Quantifier Modeling and Curriculum Learning
Sayan Ghosh, Rakesh R Menon, Shashank Srivastava
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Learning from Natural Language Feedback
Jérémy Scheurer, Jon Ander Campos, Jun Shern Chan, Angelica Chen, Kyunghyun Cho, Ethan Perez
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
When Can Models Learn From Explanations? A Formal Framework for Understanding the Roles of Explanation Data
Peter Hase, Mohit Bansal
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Linguistic communication as (inverse) reward design
Theodore Sumers, Robert D. Hawkins, Mark K Ho, Thomas L. Griffiths, Dylan Hadfield-Menell
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Using Natural Language to Guide Meta-Learning Agents towards Human-like Inductive Biases
Sreejan Kumar, Ishita Dasgupta, Michael Hu, Raja Marjieh, Robert D. Hawkins, Nathaniel Daw, Jonathan Cohen, Karthik R Narasimhan, Thomas L. Griffiths
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Conversational Grounding as Natural Language Supervision -- the need for divergent agent data
Oliver Lemon
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Semantic Supervision: Enabling Generalization over Output Spaces
Ameet Deshpande, Austin W. Hanjie, Karthik R Narasimhan
- 13 Mar 2022 (modified: 12 Mar 2024)
- LNLS
- Readers: Everyone
CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations
Rakesh R Menon, Sayan Ghosh, Shashank Srivastava
- 13 Mar 2022 (modified: 12 Mar 2024)
- LNLS
- Readers: Everyone
Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions
Alicia Parrish, Harsh Trivedi, Ethan Perez, Angelica Chen, Nikita Nangia, Jason Phang, Samuel R. Bowman
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
GrammarSHAP: An Efficient Model-Agnostic and Structure-Aware NLP Explainer
Edoardo Mosca, Defne Demirtürk, Luca Mülln, Fabio Raffagnato, Georg Groh
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Fixing Model Bugs with Natural Language Patches
Shikhar Murty, Christopher D Manning, Scott Lundberg, Marco Tulio Ribeiro
- 13 Mar 2022 (modified: 12 Mar 2024)
- LNLS
- Readers: Everyone
Prompts and Pre-Trained Language Models for Offline Reinforcement Learning
Denis Tarasov, Vladislav Kurenkov, Sergey Kolesnikov
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Predicting Human Similarity Judgments Using Large Language Models
Raja Marjieh, Ilia Sucholutsky, Theodore Sumers, Nori Jacoby, Thomas L. Griffiths
- 13 Mar 2022 (modified: 12 Mar 2024)
- LNLS
- Readers: Everyone
Finding Sub-task Structure with Natural Language Instruction
Ryokan Ri, Yufang Hou, Radu Marinescu, Akihiro Kishimoto
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone
Distilling Hypernymy Relations from Language Models: On the Effectiveness of Zero-Shot Taxonomy Induction
Devansh Jain, Luis Espinosa-Anke
- 13 Mar 2022 (modified: 05 May 2023)
- LNLS
- Readers: Everyone