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Found 8 papers, 2 papers with code
On the Efficacy of Text-Based Input Modalities for Action Anticipation
Compared to existing methods, MAT has the advantage of learning additional environmental context from two kinds of text inputs: action descriptions during the pre-training stage, and the text inputs for detected objects and actions during modality feature fusion.
End-to-End Query Term Weighting
These inferred weights and terms can be used directly by a retrieval system to perform a query search.
Ranked #1 on
Passage Retrieval
on MS MARCO
Learning Temporal Rules from Noisy Timeseries Data
Events across a timeline are a common data representation, seen in different temporal modalities.
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning
Deep learning and symbolic reasoning are complementary techniques for an intelligent system.
ProTo: Program-Guided Transformer for Program-Guided Tasks
Furthermore, we propose the Program-guided Transformer (ProTo), which integrates both semantic and structural guidance of a program by leveraging cross-attention and masked self-attention to pass messages between the specification and routines in the program.
Ranked #1 on
Visual Question Answering (VQA)
on GQA test-std
Neural Temporal Logic Programming
Events across a timeline are a common data representation, seen in different temporal modalities.
How to Design Sample and Computationally Efficient VQA Models
In multi-modal reasoning tasks, such as visual question answering (VQA), there have been many modeling and training paradigms tested.
Differentiable End-to-End Program Executor for Sample and Computationally Efficient VQA
We present a differentiable end-to-end program executor (DePe), which addresses Visual Question Answering (VQA) in a sample and computationally efficient manner.
