Ashwin Kalyan

Orcid: 0009-0006-3448-3305

According to our database1, Ashwin Kalyan authored at least 29 papers between 2018 and 2024.

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Bibliography

2024
PersonaGym: Evaluating Persona Agents and LLMs.
CoRR, 2024

Deception in Reinforced Autonomous Agents: The Unconventional Rabbit Hat Trick in Legislation.
CoRR, 2024

RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs.
CoRR, 2024

QualEval: Qualitative Evaluation for Model Improvement.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

GEO: Generative Engine Optimization.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Estimating Numbers without Regression.
CoRR, 2023

Distraction-free Embeddings for Robust VQA.
CoRR, 2023

Exploiting Generalization in Offline Reinforcement Learning via Unseen State Augmentations.
CoRR, 2023

CSTS: Conditional Semantic Textual Similarity.
CoRR, 2023

Anthropomorphization of AI: Opportunities and Risks.
CoRR, 2023

RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs.
CoRR, 2023

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Let GPT be a Math Tutor: Teaching Math Word Problem Solvers with Customized Exercise Generation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Toxicity in chatgpt: Analyzing persona-assigned language models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

C-STS: Conditional Semantic Textual Similarity.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
ProKnow: Process knowledge for safety constrained and explainable question generation for mental health diagnostic assistance.
Frontiers Big Data, 2022

SPARTAN: Sparse Hierarchical Memory for Parameter-Efficient Transformers.
CoRR, 2022

Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering.
CoRR, 2022

Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

LILA: A Unified Benchmark for Mathematical Reasoning.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Model-Advantage Optimization for Model-Based Reinforcement Learning.
CoRR, 2021

Programming Puzzles.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

How much coffee was consumed during EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2019
Trainable Decoding of Sets of Sequences for Neural Sequence Models.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations.
Proceedings of the 35th International Conference on Machine Learning, 2018

Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018


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