Combining large language models with enterprise knowledge graphs: a perspective on enhanced natural language understanding
Knowledge Graphs (KGs) have revolutionized knowledge representation, enabling a graph-
structured framework where entities and their interrelations are systematically organized …
structured framework where entities and their interrelations are systematically organized …
CTINEXUS: Leveraging Optimized LLM In-Context Learning for Constructing Cybersecurity Knowledge Graphs Under Data Scarcity
Textual descriptions in cyber threat intelligence (CTI) reports, such as security articles and
news, are rich sources of knowledge about cyber threats, crucial for organizations to stay …
news, are rich sources of knowledge about cyber threats, crucial for organizations to stay …
Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models
Aligning Large Language Models (LLMs) traditionally relies on costly training and human
preference annotations. Self-alignment seeks to reduce these expenses by enabling models …
preference annotations. Self-alignment seeks to reduce these expenses by enabling models …
Fewer is More: Boosting Math Reasoning with Reinforced Context Pruning
Abstract Large Language Models (LLMs) have shown impressive capabilities, yet they still
struggle with math reasoning. In this work, we propose CoT-Influx, a novel approach that …
struggle with math reasoning. In this work, we propose CoT-Influx, a novel approach that …
Just Read the Codebook! Make Use of Quality Codebooks in Zero-Shot Classification of Multilabel Frame Datasets
M Ruckdeschel - … of the 31st International Conference on …, 2025 - aclanthology.org
The recent development of Large Language Models lowered the barrier to entry for using
Natural Language Processing methods for various tasks in the related scientific field of …
Natural Language Processing methods for various tasks in the related scientific field of …
Prediction of tumor board procedural recommendations using large language models
Introduction Multidisciplinary tumor boards are meetings where a team of medical
specialists, including medical oncologists, radiation oncologists, radiologists, surgeons, and …
specialists, including medical oncologists, radiation oncologists, radiologists, surgeons, and …
Fusing AI: Multimodal Language Models Inference Across Diverse Inputs
Despite the various hurdles multimodal language models (MLMs) face, their broad
applicability outweighs the implementation effort. As MLM technologies advance, they will …
applicability outweighs the implementation effort. As MLM technologies advance, they will …
Revisiting the Superficial Alignment Hypothesis
The Superficial Alignment Hypothesis posits that almost all of a language model's abilities
and knowledge are learned during pre-training, while post-training is about giving a model …
and knowledge are learned during pre-training, while post-training is about giving a model …