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cs.CL2025

PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory

Bowen Jiang, Yuan Yuan, Maohao Shen +13

Personalization is one of the next milestones in advancing AI capability and alignment. We introduce PersonaMem-v2, the state-of-the-art dataset for LLM personalization that simula…

cs.AI2025

CoDA: Agentic Systems for Collaborative Data Visualization

Zichen Chen, Jiefeng Chen, Sercan Ö. Arik +3

Deep research has revolutionized data analysis, yet data scientists still devote substantial time to manually crafting visualizations, highlighting the need for robust automation f…

q-fin.GN2025

Standard Benchmarks Fail -- Auditing LLM Agents in Finance Must Prioritize Risk

Zichen Chen, Jiaao Chen, Jianda Chen +1

Standard benchmarks fixate on how well large language model (LLM) agents perform in finance, yet say little about whether they are safe to deploy. We argue that accuracy metrics an…

cs.AI2025

GraphEval36K: Benchmarking Coding and Reasoning Capabilities of Large Language Models on Graph Datasets

Qiming Wu, Zichen Chen, Will Corcoran +2

Large language models (LLMs) have achieved remarkable success in natural language processing (NLP), demonstrating significant capabilities in processing and understanding text data…

cs.HC2025

Agentic Workflows for Conversational Human-AI Interaction Design

Arthur Caetano, Kavya Verma, Atieh Taheri +5

Conversational human-AI interaction (CHAI) have recently driven mainstream adoption of AI. However, CHAI poses two key challenges for designers and researchers: users frequently ha…

cs.HC2025

Engaging with AI: How Interface Design Shapes Human-AI Collaboration in High-Stakes Decision-Making

Zichen Chen, Yunhao Luo, Misha Sra

As reliance on AI systems for decision-making grows, it becomes critical to ensure that human users can appropriately balance trust in AI suggestions with their own judgment, espec…