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cs.CL2024
Instruction Embedding: Latent Representations of Instructions Towards Task Identification
Yiwei Li, Jiayi Shi, Shaoxiong Feng +6
Instruction data is crucial for improving the capability of Large Language Models (LLMs) to align with human-level performance. Recent research LIMA demonstrates that alignment is…
cs.AI2024
Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents
Jinyang Li, Nan Huo, Yan Gao +7
Interactive Data Analysis, the collaboration between humans and LLM agents, enables real-time data exploration for informed decision-making. The challenges and costs of collecting…