Asif Ekbal

Indian Institute of Technology Patna | IIT Patna · Department of Computer Science and Engineering

Given the advancements in conversational artificial intelligence, the evaluation and assessment of Large Language Models (LLMs) play a crucial role in ensuring optimal performance across various conversational tasks. In this paper, we present a comprehensive study that thoroughly evaluates the capabilities and limitations of five prevalent LLMs: Ll...

Hate speech, offensive language, aggression, racism, sexism, and other abusive language are common phenomena in social media. There is a need for Artificial Intelligence(AI)based intervention which can filter hate content at scale. Most existing hate speech detection solutions have utilized the features by treating each post as an isolated input in...

In Medical question-answering (QA) tasks, the need for effective systems is pivotal in delivering accurate responses to intricate medical queries. However, existing approaches often struggle to grasp the intricate logical structures and relationships inherent in medical contexts, thus limiting their capacity to furnish precise and nuanced answers....

Detecting offensive memes is crucial, yet standard deep neural network systems often remain opaque. Various input attribution-based methods attempt to interpret their behavior, but they face challenges with implicitly offensive memes and non-causal attributions. To address these issues, we propose a framework based on a Structural Causal Model (SCM...

The integrity of the peer-review process is vital for maintaining scientific rigor and trust within the academic community. With the steady increase in the usage of large language models (LLMs) like ChatGPT in academic writing, there is a growing concern that AI-generated texts could compromise scientific publishing, including peer-reviews. Previou...

Previous studies on question generation from videos have mostly focused on generating questions about common objects and attributes and hence are not entity-centric. In this work, we focus on the generation of entity-centric information-seeking questions from videos. Such a system could be useful for video-based learning, recommending ``People Also...

In recent years, there has been a significant rise in the phenomenon of hate against women on social media platforms, particularly through the use of misogynous memes. These memes often target women with subtle and obscure cues, making their detection a challenging task for automated systems. Recently, Large Language Models (LLMs) have shown promis...

Researchers have found that fake news spreads much times faster than real news. This is a major problem, especially in today's world where social media is the key source of news for many among the younger population. Fact verification, thus, becomes an important task and many media sites contribute to the cause. Manual fact verification is a tediou...

Code-mixing refers to switching between two or more languages within the same utterance, which is very prevalent in multilingual societies. The amount of code-mixed content has increased due to the spike in multilingual users on review platforms. Analyzing these reviews can be beneficial for both consumers and service providers. Aspect category (AC...

Sarcasm detection in unimodal or multimodal setting is a very complex task. Sarcasm, emotion, and sentiment are related to each other, and hence any multitask model could be an effective way to leverage the interdependence among these tasks. In order to better represent these clandestine associations, we avoid solely relying on traditional machine...

Politeness is key to successful conversations. It depicts the behavior that is socially valued and is often accompanied by emotions. Previously, researchers have focused on detecting politeness in goal-oriented conversations in high-resource English language. The existing studies do not focus on identifying politeness in a resource-scared Indian la...

"An idea is nothing more nor less than a new combination of old elements" (Young, J.W.). The widespread adoption of Large Language Models (LLMs) and publicly available ChatGPT have marked a significant turning point in the integration of Artificial Intelligence (AI) into people's everyday lives. This study explores the capability of LLMs in generat...

In an era where language biases contribute to societal inequalities, this research focuses on gender bias in textual data, with profound implications for promoting inclusivity and equity, aligning with United Nations Sustainable Development Goals (SDGs) and upholding the principle of Leave No One Behind (LNOB). Leveraging advances in artificial int...

Memes, initially created for humor and social commentary, have transformed into platforms for offensive online content. Detecting such content is crucial; however, existing deep learning-based meme offensiveness classifiers lack transparency, functioning as opaque black-box systems. While Integrated Gradient and similar input-attribution interpreta...

Humour detection has attracted considerable attention due to its significance in interpreting dialogues across text, visual, and acoustic modalities. However, effective methods to map correlations among different modalities remain an active area of research. In this study, we go beyond traditional machine learning techniques by introducing a Variat...

In document-level neural machine translation (DocNMT), multi-encoder approaches are common in encoding context and source sentences. Recent studies \cite{li-etal-2020-multi-encoder} have shown that the context encoder generates noise and makes the model robust to the choice of context. This paper further investigates this observation by explicitly...

Computational approach to politeness is the task of automatically predicting and generating politeness in text. This is a pivotal task for conversational analysis, given the ubiquity and challenges of politeness in interactions. The computational approach to politeness has witnessed great interest from the conversational analysis community. This ar...

Recognizing humor in meme data is a challenging task in natural language processing (NLP) and computer vision (CV) due to the complexity and variability of humor. With the explosive growth of Internet memes on social media platforms such as Facebook, Twitter, and Instagram, this task has become more important. However, there have been few studies t...

In the era of social media, the use of emojis and code-mixed language has become essential in online communication. However, selecting the appropriate emoji that matches a particular sentiment or emotion in the code-mixed text can be difficult. This paper presents a novel task of predicting multiple emojis in English-Hindi code-mixed sentences and...

Computational approach to politeness is the task of automatically predicting and/or generating politeness in text. This is a pivotal task for conversational analysis, given the ubiquity and challenges of politeness in interactions. The computational approach to politeness has witnessed great interest from the conversational analysis community. This...

Sarcasm is a widespread linguistic phenomenon that poses a considerable challenge to explain due to its subjective nature, absence of contextual cues, and rooted personal perspectives. Even though the identification of sarcasm has been extensively studied in dialogue analysis, merely detecting sarcasm falls short of enabling conversational systems...

In the digital age, cybercrimes, particularly cyber harassment, have become pressing issues, targeting vulnerable individuals like children, teenagers, and women. Understanding the experiences and needs of the victims is crucial for effective support and intervention. Online conversations between victims and virtual harassment counselors (chatbots)...

Affective computing involves examining and advancing systems and devices capable of identifying, comprehending, processing, and emulating human emotions, sentiment, politeness and personality characteristics. This is an ever-expanding multidisciplinary domain that investigates how technology can contribute to the comprehension of human affect, how...

Memes, a prevalent form of online communication, often express opinions, emotions, and creativity concisely and entertainingly. Amidst the diverse landscape of memes, the realm of sarcastic memes holds a unique position with its foundation in irony, mockery, satire, and messages that diverge from literal meanings. Detecting sarcasm in memes is chal...

The method of translation from one language to another without human intervention is known as Machine Translation (MT). Multilingual neural machine translation (MNMT) is a technique for MT that builds a single model for multiple languages. It is preferred over other approaches since it decreases training time and improves translation in low-resourc...

Producing a high-quality review translation is a multifaceted process. It goes beyond successful semantic transfer and requires conveying the original message’s tone and style in a way that resonates with the target audience, whether they are human readers or Natural Language Processing (NLP) applications. Capturing these subtle nuances of the revi...

The peer-review process plays a pivotal role in maintaining the quality and credibility of scientific publications. However, in recent times, there has been an increase in unhelpful and overly critical reviews, which can be detrimental to the process. This surge in unconstructive reviews can be attributed to a higher volume of paper submissions and...

Poor health is one of the fundamental causes behind the suffering and deprivation of human beings. One of the United Nations (UN) Sustainable Development Goals is to enhance the quality of healthcare for everyone, which includes economic coverage, availability of high-quality fundamental health-care services, and access to proper, efficient, high-q...

Medical question-answering systems require the ability to extract accurate, concise, and comprehensive answers. They will better comprehend the complex text and produce helpful answers if they can reason on the explicit constraints described in the question’s textual context and the implicit, pertinent knowledge of the medical world. Integrating Kn...

The growing volume of scientific literature makes it difficult for researchers to identify the key contributions of a research paper. Automating this process would facilitate efficient understanding, faster literature surveys and comparisons. The automated process may help researchers to identify relevant and impactful information in less time and...

Detecting texts that contain semantic-level new information is not straightforward. The problem becomes more challenging for research articles. Over the years, many datasets and techniques have been developed to attempt automatic novelty detection. However, the majority of the existing textual novelty detection investigations are targeted toward ge...

This paper tackles the critical challenge of detecting and mitigating unintended political bias in offensive meme detection. Political memes are a powerful tool that can be used to influence public opinion and disrupt voters’ mindsets. However, current visual-linguistic models for offensive meme detection exhibit unintended bias and struggle to acc...

In a persuasive conversation for social good , even the most compelling and persuasive argument may fail to persuade a persuadee resisting the persuasion. Whereas use of polite tone, apologetic expressions, or deferential modes of reference such as, ’thank you’, ’Please’ etc. can make the conversation more interesting, engaging, and persuading to...

Social media platforms have become an open door for users to share their views, resulting in a growing trend of offensive content being shared on social media. Detecting and addressing offensive content is crucial due to its significant impact on society. Although there has been extensive research on the detection of offensive content in the Englis...

Scientific article summarization poses a challenge because the interpretability of the article depends on the objective, experience of the reader. Editors/Chairs assign experts in the domain as peer reviewers. These experts often write a summary of the article at the beginning of their reviews which offers a summarized view of their understanding (...

Knowledge-grounded dialogue generation is the process of formulating an informed response based on both the conversation context and external knowledge. Multi-modality in dialogue systems has paved the way for more robust conversational bots. Any multi-modal system seeks to bridge the gap between language and vision by combining information from im...

Peer reviews are intended to give authors constructive and informative feedback. It is expected that the reviewers will make constructive suggestions over certain aspects, e.g., novelty, clarity, empirical and theoretical soundness, etc., and sections, e.g., problem definition/idea, datasets, methodology, experiments , results, etc., of the paper i...

Online news consumption via social media platforms has accelerated the growth of digital journalism. Adverse to traditional media, digital media has lower entry barriers and allows everyone as a content creator, resulting in numerous fake news productions to attract public attention. As multimedia content is more convenient for users than expressin...

Analyzing memes on the internet has emerged as a crucial endeavor due to the impact this multi-modal form of content wields in shaping online discourse. Memes have become a powerful tool for expressing emotions and sentiments, possibly even spreading hate and misinformation, through humor and sarcasm. In this paper, we present the overview of the M...

In recent times, there has been tremendous growth in the number of multi-lingual users on social media platforms. Consequently, the code-mixing phenomenon, i.e., mixing of more than one language, has become ubiquitous in Internet content. In this paper, we present a shared-private, multi-lingual, multi-task model coupled with a transformer-based pr...

During a conversation, it is critical for participants to establish what they both agree on, also known as the common ground. Grounding implies recognizing that the listener has understood what the speaker has said, considering several factors. This can be accomplished by basing dialog models on various features like aspects, sentiments, images, an...

Analyzing memes on the internet has emerged as a crucial endeavor due to the impact this multi-modal form of content wields in shaping online discourse. Memes have become a powerful tool for expressing emotions and sentiments, possibly even spreading hate and misinformation, through humor and sarcasm. In this paper, we present the overview of the M...

The study investigates the effectiveness of utilizing multimodal information in Neural Machine Translation (NMT). While prior research focused on using multimodal data in low-resource scenarios, this study examines how image features impact translation when added to a large-scale, pre-trained unimodal NMT system. Surprisingly, the study finds that...

Recent studies have shown that the multi-encoder models are agnostic to the choice of context, and the context encoder generates noise which helps improve the models in terms of BLEU score. In this paper, we further explore this idea by evaluating with context-aware pronoun translation test set by training multi-encoder models trained on three diff...

With social media usage growing exponentially in the past few years, fake news has also become extremely prevalent. The detrimental impact of fake news emphasizes the need for research focused on automating the detection of false information and verifying its accuracy. In this work, we present the outcome of the Factify 2 shared task, which provide...

With social media usage growing exponentially in the past few years, fake news has also become extremely prevalent. The detrimental impact of fake news emphasizes the need for research focused on automating the detection of false information and verifying its accuracy. In this work, we present the outcome of the Factify 2 shared task, which provide...

One key frontier of artificial intelligence (AI) is the ability to comprehend research articles and validate their findings, posing a magnanimous problem for AI systems to compete with human intelligence and intuition. As a benchmark of research validation, the existing peer-review system still stands strong despite being criticized at times by man...

Natural Language Understanding (NLU) and Natural Language Generation (NLG) are the two critical components of every conversational system that handles the task of understanding the user by capturing the necessary information in the form of slots and generating an appropriate response in accordance with the extracted information. Recently, dialogue...

The potential for conversational agents offering mental health and legal counseling in an autonomous, interactive, and vitally accessible environment is getting highlighted due to the increased access to information through the internet and mobile devices. A counseling conversational agent should be able to offer higher engagement mimicking the rea...

Data-driven supervised approaches rely on the parallel corpus. Due to lack of data and resources availability, it has become more difficult to achieve accurate outputs. In addition, the efficiency of the machine translation system depends on the quality of the used corpora. Hindi still lacks good quality parallel corpora and needs more resources fo...

With the growing presence of multimodal content on the web, a specific category of fake news is rampant on popular social media outlets. In this category of fake online information, real multimedia contents (images, videos) are used in different but related contexts with manipulated texts to mislead the readers. The presence of seemingly non-manipu...

Natural Language Understanding (NLU) and Natural Language Generation (NLG) are the two critical components of every conversational system that handles the task of understanding the user by capturing the necessary information in the form of slots and generating an appropriate response in accordance with the extracted information. Recently, dialogue...

In this paper, we propose an end-to-end system for unsupervised text style transfer (UTST). Prior studies on UTST work on the principle of disentanglement between style and content features, which successfully accomplishes the task of generating style-transferred text. The success of a style transfer system depends on three criteria, viz. Style tra...

Even though peer review is a central aspect of scientific communication, research shows that the process reveals a power imbalance. The position of the reviewer allows them to be harsh and intentionally offensive without being held accountable. It casts doubt on the integrity of the peer-review process and transforms it into an unpleasant and traum...

Emotion classification along with sentimental analysis in dialogues is a complex task that has currently attained immense popularity. When communicating their thoughts and feelings, humans are prone to having many emotions of varying intensities. The task is complicated and fascinating since emotions in a dialogue utterance can be independent or ba...