Demo Data from EDBT 2026 / reviewers in the wild / expert
Victor De Lima
dblp:401/6394
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 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 |
Question answering and dialogue systems · 33% Planning, search and constraint satisfaction · 33% Robot manipulation · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Question answering and dialogue systems
conversational agents |
1.0 | 1 | 2026 | YIELD: A Large-Scale Dataset and Evaluation Framework for Information Elicitation Agents · ACL (1) 2026 |
Robotics › Robot manipulation › robot design › mechanism design
information elicitation |
1.0 | 1 | 2026 | YIELD: A Large-Scale Dataset and Evaluation Framework for Information Elicitation Agents · ACL (1) 2026 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning under uncertainty
partially observable markov decision process |
1.0 | 1 | 2026 | YIELD: A Large-Scale Dataset and Evaluation Framework for Information Elicitation Agents · ACL (1) 2026 |
Methods — techniques the papers use, named apart from their topics
large language model fine-tuning · 1.0POMDP · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | YIELD: A Large-Scale Dataset and Evaluation Framework for Information Elicitation AgentsabstractMost conversational agents (CAs) are designed to satisfy user needs through user-driven interactions.However, many real-world settings, such as academic interviewing, judicial proceedings, and journalistic investigations, involve broader institutional decision-making processes and require agents that can elicit information from users.In this paper, we introduce Information Elicitation Agents (IEAs) in which the agent's goal is to elicit information from users to support the agent's institutional or task-oriented objectives.To enable systematic research on this setting, we present YIELD, a 26M-token dataset of 2,281 ethically sourced, human-to-human dialogues.Moreover, we formalize information elicitation as a finite-horizon POMDP and propose novel metrics tailored to IEAs.Pilot experiments on multiple foundation LLMs show that training on YIELD improves their alignment with real elicitation behavior and findings are corroborated by human evaluation.We release YIELD under CC BY 4.0.The dataset, project code, evaluation tools, and finetuned model adapters are available at: https: //github.com/infosenselab/yield. Oral History (Oglesby, 2009)Judicial Proceeding (Supreme Court of the USA, 2024)Elicitor: "OK, then think back to when you went into the Peace Corps.What were you doing the year before you went in?" Respondent: "I was in high school when I went in.I was one of the eighteen year olds that went into the Peace Corps."Elicitor: "Did you have any particular country or any place that you wanted to go?" Respondent: "South America always had a calling for me.I didn't have any particular country at all."Elicitor: "Is there any aspect of social media that you think is protected by the First Amendment?"Respondent: "Yes, Your Honor.I can certainly imagine platforms that would be subject to this law that indeed have First Amendment rights."Elicitor: "But why is it different?"Respondent: "Well -well, there's a lot in there, Your Honor.Maybe I can start with the Hurley case."Academic Interview (Taherzadeh, 2016) Journalistic Investigation (Van Susteren, 2018)Elicitor: "I was just wondering your opinion on whether biodiversity offsetting is likely to lead to more stringent or less stringent regulations around infrastructure projects?"Respondent: "It's ill-informed people not understanding the system properly because at the end of the day biodiversity offsetting doesn't affect any existing protections."Elicitor: "What's been the reception of businesses to biodiversity offsetting extending the mitigation hierarchy?"Respondent: "Well, the reception that I've had when I've been speaking to them has been really quite positive." Victor De Lima, Grace Hui Yang |
ACL (1) | 1 |