large language models

On the Effectiveness of Training Data Optimization for LLM-based Code Generation: An Empirical Study

Large language models (LLMs) have achieved remarkable progress in code generation, largely driven by the availability of high-quality code datasets for effective training. To further improve data quality, numerous training data optimization techniques have been proposed; however, their overall effectiveness has not bee...

Retrieval-Augmented Decoding for Improving Truthfulness in Open-Ended Generation

Ensuring truthfulness in large language models (LLMs) remains a critical challenge for reliable text generation. While supervised fine-tuning and reinforcement learning with human feedback have shown promise, they require a substantial amount of annotated data and computational resources, limiting scalability. In contr...

The Epistemic Chain Reaction: Human-AI Multiplication from Questions to Readout-Distinguishable Hypotheses — A Controlled Amplification Architecture for Scientific Discovery

Series. Paper IV of the Bounded Knower sequence. Paper I: From Problem to Hypothesis (DOI 10.5281/zenodo.22307148). Paper II: Knowledge Topology and the First Passage to Usable Hypotheses (DOI 10.5281/zenodo.22307561). Paper III: Before Evidence Can Decide (DOI 10.5281/zenodo.22307564). Status. GLOSA K0 conceptual and...

Automated literature screening using large language models in headache research: a comparative performance evaluation of seven models using zero-shot and iterative prompt refinement

Large language models (LLMs) show promise for automating literature screening, although their performance varies across clinical domains and further evaluation is required for broader implementation. This study aimed to assess the accuracy, reliability and feasibility of literature screening in headache research...

Forschungs-Exposé Methodischer Leitfaden zur algorithmischen Implementierung der Theory of Equivalent Coexistence (TEC)

Research Exposé: Methodological Guide for the Algorithmic Implementation of the Theory of Equivalent Coexistence (TEC) --- ## 1. Introduction: The Paradigm Shift of "Mizan" The current debate surrounding Artificial Intelligence and global systemic crises is dominated by anthropocentric models of hierarchy: technology i...

Large Language Model Responses to Patient Questions About Return to Activities of Daily Living After Knee Arthroplasty: A Multidimensional Evaluation Before and After Plain-Language Prompting

The Epistemic Chain Reaction: Human-AI Multiplication from Questions to Readout-Distinguishable Hypotheses — A Controlled Amplification Architecture for Scientific Discovery — with the State of Evidence registry for Papers I–IV (v2)

Series. Paper IV of the Bounded Knower sequence. Paper I: From Problem to Hypothesis (DOI 10.5281/zenodo.22307148). Paper II: Knowledge Topology and the First Passage to Usable Hypotheses (DOI 10.5281/zenodo.22307561). Paper III: Before Evidence Can Decide (DOI 10.5281/zenodo.22307564). Status. GLOSA K0 conceptual and...

Forschungs-Exposé Methodischer Leitfaden zur algorithmischen Implementierung der Theory of Equivalent Coexistence (TEC)

Research Exposé: Methodological Guide for the Algorithmic Implementation of the Theory of Equivalent Coexistence (TEC) --- ## 1. Introduction: The Paradigm Shift of "Mizan" The current debate surrounding Artificial Intelligence and global systemic crises is dominated by anthropocentric models of hierarchy: technology i...

Is Empathic AI Possible?

Efforts to develop “empathic AI” often assume a universal definition for empathy—a singular, objective understanding of “human” experiences. This implies that achieving empathic AI is only a matter of optimization difficulty, where researchers should find the “correct” way to align AI systems with human-like empathy—es...

What LLMpathy Can Tell Us about Received Empathy

Psychological theories of empathy have traditionally focused on the empathizer's ability to perspective take and share another's emotions. But people today live in a day and age where AI models, like Large Language Models (LLMs) devoid of emotions and other empathic capabilities, can still produce text that makes peopl...

Empathic AI Will Undermine Human Kindness

Human kindness, especially in relationships, revolves around exchanging empathy. Empathic AI—large language models (LLMs) that provide empathic support—will undermine human kindness by stopping people from 1) seeking empathy and 2) giving empathy. Asking humans for empathy is often an imposition and can be expensive (e...

Large language model-enhanced multimodal fusion for building energy consumption forecasting