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Found 6 papers, 1 papers with code
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Also, we show that compared to natural language, pseudocode can better guide the reasoning of LMs, even though they are trained to follow natural language instructions.
Commonsense-augmented Memory Construction and Management in Long-term Conversations via Context-aware Persona Refinement
As the pioneer of persona expansion in multi-session settings, our framework facilitates better response generation via human-like persona refinement.
Large Language Models are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales
Specifically, we address the clinical reasoning for disease diagnosis, where the LLM generates diagnostic rationales providing its insight on presented patient data and the reasoning path towards the diagnosis, namely Clinical Chain-of-Thought (Clinical CoT).
Coffee: Boost Your Code LLMs by Fixing Bugs with Feedback
Hence, the focus of our work is to leverage open-source code LLMs to generate helpful feedback with correct guidance for code editing.
Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents
Hence, our focus is to facilitate such multi-hop reasoning over a dialogue context, namely dialogue chain-of-thought (CoT) reasoning.
Evidence-empowered Transfer Learning for Alzheimer's Disease
To address this, we present evidence-empowered transfer learning for AD diagnosis.
