Demo Data from EDBT 2026 / reviewers in the wild / expert
Priyam Sahoo
dblp:313/5361
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2026
0009-0009-9160-5876ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Language models and text generation · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Program synthesis and code generation · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Language models and text generation › alignment
LLM behavior control |
1.0 | 1 | 2026 | DialDefer: A Framework for Detecting and Mitigating LLM Dialogic Deference · ACL (1) 2026 |
Program synthesis and code generation
code generation with language models |
0.8 | 1 | 2024 | Ansible Lightspeed: A Code Generation Service for IT Automation · ASE 2024 |
Methods — techniques the papers use, named apart from their topics
large language model · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | DialDefer: A Framework for Detecting and Mitigating LLM Dialogic DeferenceabstractParisa Rabbani, Priyam Sahoo, Ruben Mathew, Aishee Mondal, Harshita Ketharaman, Nimet Beyza Bozdag, Dilek Hakkani-Tür. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026. Parisa Rabbani, Priyam Sahoo, Ruben Mathew, Aishee Mondal, Harshita Ketharaman, Nimet Beyza Bozdag, Dilek Hakkani-Tür |
ACL (1) | 2 |
| 2024 | Ansible Lightspeed: A Code Generation Service for IT AutomationabstractThe availability of Large Language Models (LLMs) which can generate code, has made it possible to create tools that improve developer productivity. Integrated development environments or IDEs which developers use to write software are often used as an interface to interact with LLMs. Although many such tools have been released, almost all of them focus on general-purpose programming languages. Domain-specific languages, such as those crucial for Information Technology (IT) automation, have not received much attention. Ansible is one such YAML-based IT automation-specific language. Ansible Lightspeed is an LLM-based service designed explicitly to generate Ansible YAML, given natural language prompt. Priyam Sahoo, Saurabh Pujar, Ganesh Nalawade, Richard Genhardt, Louis Mandel, Luca Buratti |
ASE | 1 |