Bayesian beagle

From Summary to Action: Enhancing Large Language Models for Complex Tasks with Open World APIs

Humans’ unique tool usage distinguishes them from animals. Sum2Act pipeline enhances LLMs for real-world tasks.

MIKO: Multimodal Intention Knowledge Distillation from Large Language Models for Social-Media Commonsense Discovery

social-sciences

TL;DR: Miko framework uses language and image models to uncover social media users’ intentions.

Decomposed Prompting: Unveiling Multilingual Linguistic Structure Knowledge in English-Centric Large Language Models

prompt-engineering

English-centric LLMs excel in multilingual tasks, decomposed prompting improves efficacy and efficiency in sequence labeling.

Exploring Advanced Methodologies in Security Evaluation for LLMs

prompt-engineering

Large Language Models (LLMs) have advanced language abilities but raise security and ethical concerns. Ongoing research needed.

An Iterative Associative Memory Model for Empathetic Response Generation

social-sciences

Proposed IAMM model captures associated words for empathetic response generation, validated by experiments.

Learning or Self-aligning? Rethinking Instruction Fine-tuning

social-sciences

Instruction Fine-tuning (IFT) in language models is critical, but learning additional world knowledge can have negative effects.

Few-Shot Fairness: Unveiling LLM’s Potential for Fairness-Aware Classification

social-sciences

TL;DR: Using LLMs for fairness in AI, GPT-4 shows superior accuracy and fairness.

Meta-Task Prompting Elicits Embedding from Large Language Models

prompt-engineering

MetaEOL is a new unsupervised embedding method for generating high-quality sentence embeddings from LLMs.

Automated Discovery of Integral with Deep Learning

prompt-engineering

Advancements in deep learning can deduce integrals, but AI lacks human scientific discovery ability.

Beyond Natural Language: LLMs Leveraging Alternative Formats for Enhanced Reasoning and Communication

prompt-engineering

TL;DR: Non-NL formats improve LLM reasoning efficiency and multi-agent communication.

MEGAnno+: A Human-LLM Collaborative Annotation System

social-sciences

TL;DR: Large language models and humans should collaborate for reliable data labeling. Check out MEGAnno+ for more.

Prospect Personalized Recommendation on Large Language Model-based Agent Platform

ACM article format guide for LATEX users.

Hire a Linguist!: Learning Endangered Languages with In-Context Linguistic Descriptions

social-sciences

prompt-engineering

LingoLLM enables large language models to process and translate endangered languages with linguistic knowledge.

Gradient-Free Adaptive Global Pruning for Pre-trained Language Models

social-sciences

TL;DR: AdaGP improves LLM efficiency with global pruning and modular function optimization.

Editing Factual Knowledge and Explanatory Ability of Medical Large Language Models

Model editing improves large language models for medical knowledge without affecting irrelevant information.

ChatSpamDetector: Leveraging Large Language Models for Effective Phishing Email Detection

ChatSpamDetector uses large language models to accurately detect phishing emails with detailed reasoning.

Human Simulacra: A Step toward the Personification of Large Language Models

social-sciences

TL;DR: Large language models can replace human participants in experiments, with potential for practical applications.

Towards Generalist Prompting for Large Language Models by Mental Models

prompt-engineering

Large language models need specially designed prompting methods for optimal performance. MeMo achieves this.