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From the 1 of 14 linked papers with an AI index.

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20242026
most citedScaling Knowledge Graph Construction through Synthetic Data Generation and Distillation

1 citations · 1 across the 6 of their papers we have counts for

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cs.CL2026

Dont Stop Early: Scalable Enterprise Deep Research with Controlled Information Flow and Evidence-Aware Termination

Prafulla Kumar Choubey, Kung-Hsiang Huang, Pranav Narayanan Venkit +5

Enterprise deep research often fails to produce decision-ready reports due to uneven information coverage, context explosion, and premature stopping. We propose a scalable Enterpri…

cs.CL20261 cited

Scaling Knowledge Graph Construction through Synthetic Data Generation and Distillation

Prafulla Kumar Choubey, Xin Su, Man Luo +9

Document-level knowledge graph (KG) construction faces a fundamental scaling challenge: existing methods either rely on expensive large language models (LLMs), making them economic…

cs.CL2025

Benchmarking Deep Search over Heterogeneous Enterprise Data

Prafulla Kumar Choubey, Xiangyu Peng, Shilpa Bhagavath +3

We present a new benchmark for evaluating Deep Search--a realistic and complex form of retrieval-augmented generation (RAG) that requires source-aware, multi-hop reasoning over div…

cs.CL2025

CRMArena-Pro: Holistic Assessment of LLM Agents Across Diverse Business Scenarios and Interactions

Kung-Hsiang Huang, Akshara Prabhakar, Onkar Thorat +6

While AI agents hold transformative potential in business, effective performance benchmarking is hindered by the scarcity of public, realistic business data on widely used platform…

cs.CL2025

Unanswerability Evaluation for Retrieval Augmented Generation

Xiangyu Peng, Prafulla Kumar Choubey, Caiming Xiong +1

Existing evaluation frameworks for retrieval-augmented generation (RAG) systems focus on answerable queries, but they overlook the importance of appropriately rejecting unanswerabl…

cs.CL2025

SiReRAG: Indexing Similar and Related Information for Multihop Reasoning

Nan Zhang, Prafulla Kumar Choubey, Alexander Fabbri +5

Indexing is an important step towards strong performance in retrieval-augmented generation (RAG) systems. However, existing methods organize data based on either semantic similarit…