activity
20232026
most citedAdvancements in Scientific Controllable Text Generation Methods

6 citations · 7 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2026

On Defining Erasure Harms for NLP

Yu Lu Liu, Arnav Goel, Jackie Chi Kit Cheung +3

The deployment of NLP systems has raised concerns about harms they might produce, including representational harms. Recent literature has begun to conceptualize and measure one suc…

cs.CL2026

MORPHOGEN: A Multilingual Benchmark for Evaluating Gender-Aware Morphological Generation

Mehul Agarwal, Aditya Aggarwal, Arnav Goel +2

While multilingual large language models (LLMs) perform well on high-level tasks like translation and question answering, their ability to handle grammatical gender and morphologic…

cs.IR2026

HORIZON: A Benchmark for In-the-wild User Behaviour Modeling

Arnav Goel, Pranjal A Chitale, Bhawna Paliwal +2

User behavior in the real world is diverse, cross-domain, and spans long time horizons. Existing user modeling benchmarks however remain narrow, focusing mainly on short sessions a…

cs.CV2025

Enhancing Scientific Visual Question Answering via Vision-Caption aware Supervised Fine-Tuning

Janak Kapuriya, Anwar Shaikh, Arnav Goel +8

In this study, we introduce Vision-Caption aware Supervised FineTuning (VCASFT), a novel learning paradigm designed to enhance the performance of smaller Vision Language Models(VLM…

cs.CL2024

Attributing Culture-Conditioned Generations to Pretraining Corpora

Huihan Li, Arnav Goel, Keyu He +1

In open-ended generative tasks like narrative writing or dialogue, large language models often exhibit cultural biases, showing limited knowledge and generating templated outputs f…

cs.CL2024★ 1 cited

Exploring Multilingual Unseen Speaker Emotion Recognition: Leveraging Co-Attention Cues in Multitask Learning

Arnav Goel, Medha Hira, Anubha Gupta

Advent of modern deep learning techniques has given rise to advancements in the field of Speech Emotion Recognition (SER). However, most systems prevalent in the field fail to gene…

cs.CL2024

Multilingual Prosody Transfer: Comparing Supervised & Transfer Learning

Arnav Goel, Medha Hira, Anubha Gupta

The field of prosody transfer in speech synthesis systems is rapidly advancing. This research is focused on evaluating learning methods for adapting pre-trained monolingual text-to…

cs.CL2024

CrossVoice: Crosslingual Prosody Preserving Cascade-S2ST using Transfer Learning

Medha Hira, Arnav Goel, Anubha Gupta

This paper presents CrossVoice, a novel cascade-based Speech-to-Speech Translation (S2ST) system employing advanced ASR, MT, and TTS technologies with cross-lingual prosody preserv…

cs.CL2024

LLMGuard: Guarding Against Unsafe LLM Behavior

Shubh Goyal, Medha Hira, Shubham Mishra +6

Although the rise of Large Language Models (LLMs) in enterprise settings brings new opportunities and capabilities, it also brings challenges, such as the risk of generating inappr…

cs.CL2023★ 6 cited

Advancements in Scientific Controllable Text Generation Methods

Arnav Goel, Medha Hira, Avinash Anand +2

The previous work on controllable text generation is organized using a new schema we provide in this study. Seven components make up the schema, and each one is crucial to the crea…