With the growing interest in large language models, the need for evaluat...
We introduce Logical Offline Cycle Consistency Optimization (LOCCO), a
s...
The sliding window approach provides an elegant way to handle contexts o...
Instruction fine-tuned language models on a collection of instruction
an...
Many information retrieval tasks require large labeled datasets for
fine...
The field of Question Answering (QA) has made remarkable progress in rec...
Neural information retrieval (IR) systems have progressed rapidly in rec...
We systematically study the calibration of classifiers trained with
diff...
Neural passage retrieval is a new and promising approach in open retriev...
Knowledge Base Question Answering (KBQA) tasks that involve complex reas...
Despite extensive research on parsing of English sentences into Abstract...
We propose a transition-based system to transpile Abstract Meaning
Repre...
AMR parsing has experienced an unprecendented increase in performance in...
Predicting linearized Abstract Meaning Representation (AMR) graphs using...
Knowledge Base Question Answering (KBQA) tasks that in-volve complex
rea...
Recent interest in Knowledge Base Completion (KBC) has led to a plethora...
We develop high performance multilingualAbstract Meaning Representation ...
Knowledge base question answering (KBQA) is an important task in Natural...
End-to-end question answering (QA) requires both information retrieval (...
Abstract Meaning Representation (AMR) parsing has experienced a notable
...
Transfer learning techniques are particularly useful in NLP tasks where ...
Knowledgebase question answering systems are heavily dependent on relati...
Abstract Meaning Representations (AMRs) are broad-coverage sentence-leve...
We introduce TechQA, a domain-adaptation question answering dataset for ...
In this paper, we introduce the problem of knowledge graph contextualiza...
Many of the top question answering systems today utilize ensembling to
i...
Existing literature on Question Answering (QA) mostly focuses on algorit...
This paper introduces a novel orchestration framework, called CFO
(COMPU...
Our work involves enriching the Stack-LSTM transition-based AMR parser
(...
We propose and compare various sentence selection strategies for active
...