23 citations · 86 across the 16 of their papers we have counts for
16 papers
Automatic Image-Level Morphological Trait Annotation for Organismal Images
Vardaan Pahuja, Samuel Stevens, Alyson East +2
Morphological traits are physical characteristics of biological organisms that provide vital clues on how organisms interact with their environment. Yet extracting these traits rem…
Explorer: Scaling Exploration-driven Web Trajectory Synthesis for Multimodal Web Agents
Vardaan Pahuja, Yadong Lu, Corby Rosset +5
Recent success in large multimodal models (LMMs) has sparked promising applications of agents capable of autonomously completing complex web tasks. While open-source LMM agents hav…
Fine-Tuning is Fine, if Calibrated
Zheda Mai, Arpita Chowdhury, Ping Zhang +8
Fine-tuning is arguably the most straightforward way to tailor a pre-trained model (e.g., a foundation model) to downstream applications, but it also comes with the risk of losing…
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9
Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…
Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs
Vardaan Pahuja, Weidi Luo, Yu Gu +7
Camera traps are important tools in animal ecology for biodiversity monitoring and conservation. However, their practical application is limited by issues such as poor generalizati…
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
Cheng-Hao Tu, Hong-You Chen, Zheda Mai +7
We propose a learning problem involving adapting a pre-trained source model to the target domain for classifying all classes that appeared in the source data, using target data tha…
Diversifying Joint Vision-Language Tokenization Learning
Vardaan Pahuja, AJ Piergiovanni, Anelia Angelova
Building joint representations across images and text is an essential step for tasks such as Visual Question Answering and Video Question Answering. In this work, we find that the…
A Retrieve-and-Read Framework for Knowledge Graph Link Prediction
Vardaan Pahuja, Boshi Wang, Hugo Latapie +2
Knowledge graph (KG) link prediction aims to infer new facts based on existing facts in the KG. Recent studies have shown that using the graph neighborhood of a node via graph neur…
Knowledge Base Question Answering: A Semantic Parsing Perspective
Yu Gu, Vardaan Pahuja, Gong Cheng +1
Recent advances in deep learning have greatly propelled the research on semantic parsing. Improvement has since been made in many downstream tasks, including natural language inter…
A Systematic Investigation of KB-Text Embedding Alignment at Scale
Vardaan Pahuja, Yu Gu, Wenhu Chen +4
Knowledge bases (KBs) and text often contain complementary knowledge: KBs store structured knowledge that can support long range reasoning, while text stores more comprehensive and…
Learning Sparse Mixture of Experts for Visual Question Answering
Vardaan Pahuja, Jie Fu, Christopher J. Pal
There has been a rapid progress in the task of Visual Question Answering with improved model architectures. Unfortunately, these models are usually computationally intensive due to…
Structure Learning for Neural Module Networks
Vardaan Pahuja, Jie Fu, Sarath Chandar +1
Neural Module Networks, originally proposed for the task of visual question answering, are a class of neural network architectures that involve human-specified neural modules, each…
Memory Augmented Self-Play
Shagun Sodhani, Vardaan Pahuja
Self-play is an unsupervised training procedure which enables the reinforcement learning agents to explore the environment without requiring any external rewards. We augment the se…
Reproducibility Report for "Learning To Count Objects In Natural Images For Visual Question Answering"
Shagun Sodhani, Vardaan Pahuja
This is the reproducibility report for the paper "Learning To Count Objects In Natural Images For Visual QuestionAnswering"
Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph
Amrita Saha, Vardaan Pahuja, Mitesh M. Khapra +2
While conversing with chatbots, humans typically tend to ask many questions, a significant portion of which can be answered by referring to large-scale knowledge graphs (KG). While…
Joint Learning of Correlated Sequence Labelling Tasks Using Bidirectional Recurrent Neural Networks
Vardaan Pahuja, Anirban Laha, Shachar Mirkin +3
The stream of words produced by Automatic Speech Recognition (ASR) systems is typically devoid of punctuations and formatting. Most natural language processing applications expect…