Search Results for author:
Found 10 papers, 1 papers with code
Question-Context Alignment and Answer-Context Dependencies for Effective Answer Sentence Selection
In this paper, we propose to improve the candidate scoring by explicitly incorporating the dependencies between question-context and answer-context into the final representation of a candidate.
Controlled Text Generation with Hidden Representation Transformations
We propose CHRT (Control Hidden Representation Transformation) - a controlled language generation framework that steers large language models to generate text pertaining to certain attributes (such as toxicity).
Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages
While impressive performance has been achieved on the task of Answer Sentence Selection (AS2) for English, the same does not hold for languages that lack large labeled datasets.
ACM -- Attribute Conditioning for Abstractive Multi Document Summarization
Abstractive multi document summarization has evolved as a task through the basic sequence to sequence approaches to transformer and graph based techniques.
Training Mixed-Domain Translation Models via Federated Learning
Training mixed-domain translation models is a complex task that demands tailored architectures and costly data preparation techniques.
Communication-Efficient Federated Learning for Neural Machine Translation
These new components are placed in between original layers.
Leveraging Attribute Conditioning for Abstractive Multi Document Summarization
Abstractive multi document summarization has evolved as a task through the basic sequence to sequence approaches to transformer and graph based techniques.
Deep Reinforced Self-Attention Masks for Abstractive Summarization (DR.SAS)
We have tested the limits of learning fine-grained attention in Transformers to improve the summarization quality.
BERTQA -- Attention on Steroids
Our additions to the BERT architecture augment this attention with a more focused context to query (C2Q) and query to context (Q2C) attention via a set of modified Transformer encoder units.
Biometric Signature Processing & Recognition Using Radial Basis Function Network
For testing purpose, an image is made to undergo rotation-translation-scaling correction and then given to network.
