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Found 11 papers, 3 papers with code
Towards integrated, interactive, and extensible text data analytics with Leam
From tweets to product reviews, text is ubiquitous on the web and often contains valuable information for both enterprises and consumers.
Low-resource Entity Set Expansion: A Comprehensive Study on User-generated Text
Entity set expansion (ESE) aims at obtaining a more complete set of entities given a textual corpus and a seed set of entities of a concept.
CypherBench: Towards Precise Retrieval over Full-scale Modern Knowledge Graphs in the LLM Era
Retrieval from graph data is crucial for augmenting large language models (LLM) with both open-domain knowledge and private enterprise data, and it is also a key component in the recent GraphRAG system (edge et al., 2024).
FactLens: Benchmarking Fine-Grained Fact Verification
We introduce FactLens, a benchmark for evaluating fine-grained fact verification, with metrics and automated evaluators of sub-claim quality.
A Blueprint Architecture of Compound AI Systems for Enterprise
Large Language Models (LLMs) have showcased remarkable capabilities surpassing conventional NLP challenges, creating opportunities for use in production use cases.
CMDBench: A Benchmark for Coarse-to-fine Multimodal Data Discovery in Compound AI Systems
While these systems have the potential to supplement typical analysis workflows of data analysts in enterprise data platforms, unfortunately, CASs are subject to the same data discovery challenges that analysts have encountered over the years -- silos of multimodal data sources, created across teams and departments within an organization, make it difficult to identify appropriate data sources for accomplishing the task at hand.
MEGAnno+: A Human-LLM Collaborative Annotation System
Large language models (LLMs) can label data faster and cheaper than humans for various NLP tasks.
Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions
We present a formal definition of reasoning capacity and illustrate its utility in identifying limitations within each component of the system.
Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks
We consider the task of generating knowledge-guided rationalization in natural language by using expert-written examples in a few-shot manner.
Towards Multifaceted Human-Centered AI
Human-centered AI workflows involve stakeholders with multiple roles interacting with each other and automated agents to accomplish diverse tasks.
Leam: An Interactive System for In-situ Visual Text Analysis
Text data analysis is an iterative, non-linear process with diverse workflows spanning multiple stages, from data cleaning to visualization.
