19 citations · 82 across the 39 of their papers we have counts for
4 papers · 1 filter
What's the next frontier for Data-centric AI? Data Savvy Agents
Nabeel Seedat, Jiashuo Liu, Mihaela van der Schaar
The recent surge in AI agents that autonomously communicate, collaborate with humans and use diverse tools has unlocked promising opportunities in various real-world settings. Howe…
Beyond Pointwise Scores: Decomposed Criteria-Based Evaluation of LLM Responses
Fangyi Yu, Nabeel Seedat, Dasha Herrmannova +2
Evaluating long-form answers in high-stakes domains such as law or medicine remains a fundamental challenge. Standard metrics like BLEU and ROUGE fail to capture semantic correctne…
Scales++: Compute Efficient Evaluation Subset Selection with Cognitive Scales Embeddings
Andrew M. Bean, Nabeel Seedat, Shengzhuang Chen +1
The prohibitive cost of evaluating large language models (LLMs) on comprehensive benchmarks necessitates the creation of small yet representative data subsets (i.e., tiny benchmark…
Towards Human-Guided, Data-Centric LLM Co-Pilots
Evgeny Saveliev, Jiashuo Liu, Nabeel Seedat +2
Machine learning (ML) has the potential to revolutionize various domains, but its adoption is often hindered by the disconnect between the needs of domain experts and translating t…