42 citations · 47 across the 7 of their papers we have counts for
8 papers
Does Code Cleanliness Affect Coding Agents? A Controlled Minimal-Pair Study
Priyansh Trivedi, Olivier Schmitt
As autonomous coding agents see rapid adoption, their evaluation has primarily focused on task completion rates holding the target codebase fixed. This leaves a critical question u…
Anaphora Resolution in Dialogue: System Description (CODI-CRAC 2022 Shared Task)
Tatiana Anikina, Natalia Skachkova, Joseph Renner +1
We describe three models submitted for the CODI-CRAC 2022 shared task. To perform identity anaphora resolution, we test several combinations of the incremental clustering approach…
Message Passing for Hyper-Relational Knowledge Graphs
Mikhail Galkin, Priyansh Trivedi, Gaurav Maheshwari +2
Hyper-relational knowledge graphs (KGs) (e.g., Wikidata) enable associating additional key-value pairs along with the main triple to disambiguate, or restrict the validity of a fac…
Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs
Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari +3
Question answering has emerged as an intuitive way of querying structured data sources, and has attracted significant advancements over the years. In this article, we provide an ov…
Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs
Gaurav Maheshwari, Priyansh Trivedi, Denis Lukovnikov +3
In this paper, we conduct an empirical investigation of neural query graph ranking approaches for the task of complex question answering over knowledge graphs. We experiment with s…
Formal Ontology Learning from English IS-A Sentences
Sourish Dasgupta, Ankur Padia, Gaurav Maheshwari +2
Ontology learning (OL) is the process of automatically generating an ontological knowledge base from a plain text document. In this paper, we propose a new ontology learning approa…
SimDoc: Topic Sequence Alignment based Document Similarity Framework
Gaurav Maheshwari, Priyansh Trivedi, Harshita Sahijwani +3
Document similarity is the problem of estimating the degree to which a given pair of documents has similar semantic content. An accurate document similarity measure can improve sev…
BitSim: An Algebraic Similarity Measure for Description Logics Concepts
Sourish Dasgupta, Gaurav Maheshwari, Priyansh Trivedi
In this paper, we propose an algebraic similarity measure σBS (BS stands for BitSim) for assigning semantic similarity score to concept definitions in ALCH+ an expressive fragment…