Posts by Collection

DepNeCTI: Dependency-based Nested Compound Type Identification for Sanskrit

Published in EMNLP 2023 (Findings), 2023

This paper introduces a novel task focused on identifying correct parsing and semantic relations between components of compounds in Sanskrit.

Recommended citation: Yaswanth, N., Guntupalli, S. K., & Goyal, P. (2023). "DepNeCTI: Dependency-based Nested Compound Type Identification for Sanskrit." Findings of the Association for Computational Linguistics: EMNLP 2023. https://aclanthology.org/2023.findings-emnlp.914/

DPO Kernels: A Semantically-Aware, Kernel-Enhanced, and Divergence-Rich Paradigm

Published in arXiv Preprint, 2024

This paper introduces an improved approach to direct preference optimization for language models.

Recommended citation: Yaswanth, N., et al. (2024). "DPO Kernels: A Semantically-Aware, Kernel-Enhanced, and Divergence-Rich Paradigm." arXiv preprint arXiv:2501.03271. https://arxiv.org/abs/2501.03271

YinYang-Align: Benchmarking Contradictory Objectives and Proposing Multi-Objective Optimization based DPO for Text-to-Image Alignment

Published in Under Review, 2024

This paper addresses the challenge of balancing contradictory objectives in text-to-image alignment.

Recommended citation: Yaswanth, N., et al. (2024). "YinYang-Align: Benchmarking Contradictory Objectives and Proposing Multi-Objective Optimization based DPO for Text-to-Image Alignment." arXiv preprint arXiv:2502.03512. https://arxiv.org/abs/2502.03512

II-Bench: An Image Implication Understanding Benchmark for Multimodal LLMs

Published in NeurIPS 2024 Workshop, 2024

This paper presents a benchmark for evaluating multimodal language models on image implication understanding tasks.

Recommended citation: Yaswanth, N., et al. (2024). "II-Bench: An Image Implication Understanding Benchmark for Multimodal LLMs." arXiv preprint arXiv:2406.05862. https://arxiv.org/abs/2406.05862

VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation

Published in EMNLP 2024, 2024

This paper presents an approach for automatically evaluating video generation models using simulated human feedback.

Recommended citation: Yaswanth, N., et al. (2024). "VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation." Proceedings of EMNLP 2024. https://arxiv.org/abs/2406.15252v2

Review-Feedback-Reason (ReFeR): Improving Evaluation and Reasoning through Hierarchy of Models

Published in Under Review at TMLR 2025 (Accepted at 2 NeurIPS 2024 workshops), 2024

This paper introduces a hierarchical approach to improve language model evaluation and reasoning capabilities.

Recommended citation: Yaswanth, N., et al. (2024). "Review-Feedback-Reason (ReFeR): Improving Evaluation and Reasoning through Hierarchy of Models." arXiv preprint arXiv:2407.12877. https://arxiv.org/abs/2407.12877

RADIANT - Retrieval AugmenteD entIty-context AligNmenT - Introducing RAG-ability

Published in Preprint, 2024

This paper introduces RADIANT, a novel approach for entity-context alignment in retrieval-augmented generation.

Recommended citation: Yaswanth, N., et al. (2024). "RADIANT - Retrieval AugmenteD entIty-context AligNmenT - Introducing RAG-ability."

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.