10 citations · 27 across the 24 of their papers we have counts for
26 papers
Learning Action-Effect Dynamics for Hypothetical Vision-Language Reasoning Task
Shailaja Keyur Sampat, Pratyay Banerjee, Yezhou Yang +1
'Actions' play a vital role in how humans interact with the world. Thus, autonomous agents that would assist us in everyday tasks also require the capability to perform 'Reasoning…
Learning Action-Effect Dynamics from Pairs of Scene-graphs
Shailaja Keyur Sampat, Pratyay Banerjee, Yezhou Yang +1
'Actions' play a vital role in how humans interact with the world. Thus, autonomous agents that would assist us in everyday tasks also require the capability to perform 'Reasoning…
Can Open-Domain QA Reader Utilize External Knowledge Efficiently like Humans?
Neeraj Varshney, Man Luo, Chitta Baral
Recent state-of-the-art open-domain QA models are typically based on a two stage retriever-reader approach in which the retriever first finds the relevant knowledge/passages and th…
CRIPP-VQA: Counterfactual Reasoning about Implicit Physical Properties via Video Question Answering
Maitreya Patel, Tejas Gokhale, Chitta Baral +1
Videos often capture objects, their visible properties, their motion, and the interactions between different objects. Objects also have physical properties such as mass, which the…
Pretrained Transformers Do not Always Improve Robustness
Swaroop Mishra, Bhavdeep Singh Sachdeva, Chitta Baral
Pretrained Transformers (PT) have been shown to improve Out of Distribution (OOD) robustness than traditional models such as Bag of Words (BOW), LSTMs, Convolutional Neural Network…
Hardness of Samples Need to be Quantified for a Reliable Evaluation System: Exploring Potential Opportunities with a New Task
Swaroop Mishra, Anjana Arunkumar, Chris Bryan +1
Evaluation of models on benchmarks is unreliable without knowing the degree of sample hardness; this subsequently overestimates the capability of AI systems and limits their adopti…