12 papers
From Textual Columns to Query Plans: A Unified Relational-Semantic Execution Framework for Hybrid Query Processing
Nima Shahbazi, Seiji Maekawa, Nikita Bhutani +1
Real-world table question answering often involves hybrid schemas in which some query-relevant information is explicit in relational columns, while other attributes, predicates, or…
Do Agents Need to Plan Step-by-Step? Rethinking Planning Horizon in Data-Centric Tool Calling
Naoki Otani, Nikita Bhutani, Hannah Kim +2
Explicit planning is a critical capability for LLM-based agents solving complex data-centric tasks, which require precise tool calling over external data sources. Existing strategi…
Blue Data Intelligence Layer: Streaming Data and Agents for Multi-source Multi-modal Data-Centric Applications
Moin Aminnaseri, Farima Fatahi Bayat, Nikita Bhutani +17
NL2SQL systems aim to address the growing need for natural language interaction with data. However, real-world information rarely maps to a single SQL query because (1) users expre…
Same Content, Different Representations: A Controlled Study for Table QA
Yue Zhang, Seiji Maekawa, Nikita Bhutani
Table Question Answering (Table QA) in real-world settings must operate over both structured databases and semi-structured tables containing textual fields. However, existing bench…
The Rarity Blind Spot: A Framework for Evaluating Statistical Reasoning in LLMs
Seiji Maekawa, Hayate Iso, Nikita Bhutani
Effective decision-making often relies on identifying what makes each candidate distinctive. While existing benchmarks for LLMs emphasize retrieving or summarizing information rele…
Efficient Context Selection for Long-Context QA: No Tuning, No Iteration, Just Adaptive-
Chihiro Taguchi, Seiji Maekawa, Nikita Bhutani
Retrieval-augmented generation (RAG) and long-context language models (LCLMs) both address context limitations of LLMs in open-domain question answering (QA). However, optimal exte…