11 citations · 38 across the 20 of their papers we have counts for
21 papers
Findings of the Counter Turing Test: AI-Generated Image Detection
Rajarshi Roy, Nasrin Imanpour, Ashhar Aziz +16
The rapid advancements in generative AI technologies, such as Stable Diffusion, DALL-E, and Midjourney, have significantly transformed the creation of synthetic visual content. Whi…
Findings of the Counter Turing Test: AI-Generated Text Detection
Rajarshi Roy, Gurpreet Singh, Ashhar Aziz +16
The growing capability of large language models to produce fluent, contextually coherent text has created mounting pressure on the systems and institutions responsible for ensuring…
A Comprehensive Dataset for Human vs. AI Generated Image Detection
Rajarshi Roy, Ashhar Aziz, Shashwat Bajpai +17
Multimodal generative AI systems like Stable Diffusion, DALL-E, and MidJourney have fundamentally changed how synthetic images are created. These tools drive innovation but also en…
DeHate: A Stable Diffusion-based Multimodal Approach to Mitigate Hate Speech in Images
Dwip Dalal, Gautam Vashishtha, Anku Rani +11
The rise in harmful online content not only distorts public discourse but also poses significant challenges to maintaining a healthy digital environment. In response to this, we in…
A Comprehensive Dataset for Human vs. AI Generated Text Detection
Rajarshi Roy, Gurpreet Singh, Ashhar Aziz +17
The rapid advancement of large language models (LLMs) has led to increasingly human-like AI-generated text, raising concerns about content authenticity, misinformation, and trustwo…
DPO Kernels: A Semantically-Aware, Kernel-Enhanced, and Divergence-Rich Paradigm for Direct Preference Optimization
Amitava Das, Suranjana Trivedy, Danush Khanna +8
The rapid rise of large language models (LLMs) has unlocked many applications but also underscores the challenge of aligning them with diverse values and preferences. Direct Prefer…
ViBe: A Text-to-Video Benchmark for Evaluating Hallucination in Large Multimodal Models
Vipula Rawte, Sarthak Jain, Aarush Sinha +9
Recent advances in Large Multimodal Models (LMMs) have expanded their capabilities to video understanding, with Text-to-Video (T2V) models excelling in generating videos from textu…
Overview of Factify5WQA: Fact Verification through 5W Question-Answering
Suryavardan Suresh, Anku Rani, Parth Patwa +6
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 fo…
Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training
Charles Dickens, Eddie Huang, Aishwarya Reganti +3
Graph summarization as a preprocessing step is an effective and complementary technique for scalable graph neural network (GNN) training. In this work, we propose the Coarsening Vi…
On the Relationship between Sentence Analogy Identification and Sentence Structure Encoding in Large Language Models
Thilini Wijesiriwardene, Ruwan Wickramarachchi, Aishwarya Naresh Reganti +4
The ability of Large Language Models (LLMs) to encode syntactic and semantic structures of language is well examined in NLP. Additionally, analogy identification, in the form of wo…
Overview of Memotion 3: Sentiment and Emotion Analysis of Codemixed Hinglish Memes
Shreyash Mishra, S Suryavardan, Megha Chakraborty +9
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 powerfu…
Findings of Factify 2: Multimodal Fake News Detection
S Suryavardan, Shreyash Mishra, Megha Chakraborty +9
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 rese…
ANALOGICAL -- A Novel Benchmark for Long Text Analogy Evaluation in Large Language Models
Thilini Wijesiriwardene, Ruwan Wickramarachchi, Bimal G. Gajera +6
Over the past decade, analogies, in the form of word-level analogies, have played a significant role as an intrinsic measure of evaluating the quality of word embedding methods suc…
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation
Jiong Zhu, Aishwarya Reganti, Edward Huang +4
Distributed training of GNNs enables learning on massive graphs (e.g., social and e-commerce networks) that exceed the storage and computational capacity of a single machine. To re…
Factify 2: A Multimodal Fake News and Satire News Dataset
S Suryavardan, Shreyash Mishra, Parth Patwa +9
The internet gives the world an open platform to express their views and share their stories. While this is very valuable, it makes fake news one of our society's most pressing pro…
Memotion 3: Dataset on Sentiment and Emotion Analysis of Codemixed Hindi-English Memes
Shreyash Mishra, S Suryavardan, Parth Patwa +9
Memes are the new-age conveyance mechanism for humor on social media sites. Memes often include an image and some text. Memes can be used to promote disinformation or hatred, thus…
A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering
Feng Gao, Qing Ping, Govind Thattai +3
Outside-knowledge visual question answering (OK-VQA) requires the agent to comprehend the image, make use of relevant knowledge from the entire web, and digest all the information…
Best of Both Worlds: A Hybrid Approach for Multi-Hop Explanation with Declarative Facts
Shane Storks, Qiaozi Gao, Aishwarya Reganti +1
Language-enabled AI systems can answer complex, multi-hop questions to high accuracy, but supporting answers with evidence is a more challenging task which is important for the tra…
Interactive Teaching for Conversational AI
Qing Ping, Feiyang Niu, Govind Thattai +7
Current conversational AI systems aim to understand a set of pre-designed requests and execute related actions, which limits them to evolve naturally and adapt based on human inter…
LRTA: A Transparent Neural-Symbolic Reasoning Framework with Modular Supervision for Visual Question Answering
Weixin Liang, Feiyang Niu, Aishwarya Reganti +2
The predominant approach to visual question answering (VQA) relies on encoding the image and question with a "black-box" neural encoder and decoding a single token as the answer li…
Aggression-annotated Corpus of Hindi-English Code-mixed Data
Ritesh Kumar, Aishwarya N. Reganti, Akshit Bhatia +1
As the interaction over the web has increased, incidents of aggression and related events like trolling, cyberbullying, flaming, hate speech, etc. too have increased manifold acros…