7 citations · 21 across the 9 of their papers we have counts for
9 papers
Bridge the Last-Mile Gap to Semantic Analytics: Compiling Natural-Language Queries into Semantic Operator Pipelines
Wenkai Dong, Ruyu Li, Sairam Gurajada +1
Automated AI workflows increasingly rely on natural-language reasoning over heterogeneous data, but lack a practical way to execute it through optimized semantic data systems. Rece…
Effectiveness of Prompt Optimization in NL2SQL Systems
Sairam Gurajada, Eser Kandogan, Sajjadur Rahman
NL2SQL approaches have greatly benefited from the impressive capabilities of large language models (LLMs). In particular, bootstrapping an NL2SQL system for a specific domain can b…
Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AI
Eser Kandogan, Nikita Bhutani, Dan Zhang +3
Large language models (LLMs) have gained significant interest in industry due to their impressive capabilities across a wide range of tasks. However, the widespread adoption of LLM…
A Blueprint Architecture of Compound AI Systems for Enterprise
Eser Kandogan, Sajjadur Rahman, Nikita Bhutani +11
Large Language Models (LLMs) have showcased remarkable capabilities surpassing conventional NLP challenges, creating opportunities for use in production use cases. Towards this goa…
Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language Models
Seiji Maekawa, Hayate Iso, Sairam Gurajada +1
While large language models (LMs) demonstrate remarkable performance, they encounter challenges in providing accurate responses when queried for information beyond their pre-traine…
XATU: A Fine-grained Instruction-based Benchmark for Explainable Text Updates
Haopeng Zhang, Hayate Iso, Sairam Gurajada +1
Text editing is a crucial task of modifying text to better align with user intents. However, existing text editing benchmark datasets contain only coarse-grained instructions and l…
Why are NLP Models Fumbling at Elementary Math? A Survey of Deep Learning based Word Problem Solvers
Sowmya S Sundaram, Sairam Gurajada, Marco Fisichella +2
From the latter half of the last decade, there has been a growing interest in developing algorithms for automatically solving mathematical word problems (MWP). It is a challenging…
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam +22
Knowledge Base Question Answering (KBQA) tasks that involve complex reasoning are emerging as an important research direction. However, most existing KBQA datasets focus primarily…
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam +21
Knowledge Base Question Answering (KBQA) tasks that in-volve complex reasoning are emerging as an important re-search direction. However, most KBQA systems struggle withgeneralizab…