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20242026
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cs.AI2024

Cognitive Kernel: An Open-source Agent System towards Generalist Autopilots

Hongming Zhang, Xiaoman Pan, Hongwei Wang +3

We introduce Cognitive Kernel, an open-source agent system towards the goal of generalist autopilots. Unlike copilot systems, which primarily rely on users to provide essential sta…

cs.LG2024

Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment

Rui Yang, Xiaoman Pan, Feng Luo +4

We consider the problem of multi-objective alignment of foundation models with human preferences, which is a critical step towards helpful and harmless AI systems. However, it is g…

cs.CL2024

Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models

Wenhao Yu, Hongming Zhang, Xiaoman Pan +3

Retrieval-augmented language models (RALMs) represent a substantial advancement in the capabilities of large language models, notably in reducing factual hallucination by leveragin…

cs.CL2024

Abstraction-of-Thought Makes Language Models Better Reasoners

Ruixin Hong, Hongming Zhang, Xiaoman Pan +2

Abstract reasoning, the ability to reason from the abstract essence of a problem, serves as a key to generalization in human reasoning. However, eliciting language models to perfor…

cs.CL2024

Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models

Xinran Zhao, Hongming Zhang, Xiaoman Pan +4

For a LLM to be trustworthy, its confidence level should be well-calibrated with its actual performance. While it is now common sense that LLM performances are greatly impacted by…