2 citations · 6 across the 14 of their papers we have counts for
9 papers · 1 filter
CRAFT: An Agentic Spreadsheet Form Filling System with Template Awareness
Leyao Gu, Yingjie Xiong, Zirui Tang +5
Spreadsheet form filling requires agents to consolidate external evidence, ground values to precise cells, and preserve irregular template structure. Errors in early edits can over…
Suppressing Pressure, Amplifying Evidence: Self-Guided Attention Steering to Mitigate Sycophancy and Stubbornness
Yinghao He, Mengyu Xu, Haixiang Sun +8
Reliable language models should resist unsupported user pressure while effectively using objective contextual information. However, models may exhibit sycophancy by yielding to uns…
Guarded Commits: Transactional Human Approvals for LLM Workflows
Laurent Bindschaedler, Ferdi Kossmann, Chunwei Liu +1
LLM workflows often require human approval before an irreversible external action. Most systems keep that approval outside the workflow, as an interface click or an audit entry. Th…
SemJoin: Semantic Join Optimization
Christopher Gou, Aditya Banerjee, Jiaxuan Wang +1
Integrating unstructured data into relational database systems is increasingly important as demand grows for natural language querying and analysis. A semantic join, joining two ta…
TabClean: Reusable LLM-Synthesized Programs for Tabular Data Cleaning
Yibo Wang, Riteng Zhang, Yinghao He +3
Reliable analytics and machine-learning pipelines depend on clean tabular data, yet production tables often contain missing values, typographical errors, inconsistent formats, viol…
The Table Says Otherwise: Testing LLMs with Counterfactual Relational Data
Xinzhi Wang, Chunwei Liu
Large language models (LLMs) are increasingly used to answer natural-language questions over structured data. However, when a table contains familiar real-world facts, it is unclea…
Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies
Zirui Tang, Xuanhe Zhou, Yumou Liu +19
Workspace learning requires AI agents to identify, reason over, exploit, and update explicit and implicit dependencies among heterogeneous files in a worker's workspace, enabling t…
SAGE: Selective Attention-Guided Extraction for Token-Efficient Document Indexing
Xinzhi Wang, Peter Baile Chen, Gerardo Vitagliano +5
Large language models with long context windows can answer complex questions directly from full-length academic, technical, and policy documents, but passing entire documents is of…
iPDB -- Optimizing Semantic SQL Queries
Udesh Kumarasinghe, Tyler Liu, Ahmed R. Mahmood +2
Structured Query Language (SQL) has remained the standard query language for databases. SQL is highly optimized for processing structured data laid out in relations. Meanwhile, in…