Papers by Caleb Chen Cao

3 papers
ArchiDocGen: Multi-Agent Framework for Expository Document Generation in the Architectural Industry (2025.acl-industry)

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Challenge: drafting method statements is labor-intensive and time-consuming . traditional methods involve using static templates filled in manually by engineers .
Approach: They propose a framework that automates method statement generation by using multi-agent collaboration.
Outcome: The proposed framework achieves 4.38 ContentScore, excelling in specialization, completeness, organization, and clarity.
InsightEval: An Expert-Curated Benchmark for Assessing Insight Discovery in LLM-Driven Data Agents (2026.findings-acl)

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Challenge: Existing frameworks for data analysis and insight exploration are lacking in terms of benchmarks . existing frameworks suffer from format inconsistencies, poorly conceived objectives, and redundant insights.
Approach: They propose a data-curation pipeline to construct a new dataset named InsightEval.
Outcome: The proposed benchmarks highlight prevailing challenges in automated insight discovery and raise key findings to guide future research.
VizoMem: A Visual-Textual Memory Framework for Efficient Long-Horizon Reasoning (2026.findings-acl)

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Challenge: Existing systems that use long-context modeling incur computational and memory overhead.
Approach: They propose a visual memory framework that pre-rendered text into structured images and stored as visual notes for agentic systems.
Outcome: The proposed system reduces token consumption while preserving effective long-term memory recall.

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