Results 151 to 160 of about 89,825 (246)
Look Within, Why LLMs Hallucinate: A Causal Perspective [PDF]
The emergence of large language models (LLMs) is a milestone in generative artificial intelligence, achieving significant success in text comprehension and generation tasks.
Li, He +3 more
core +1 more source
Local LLMs as a plasticity layer for fixed cloud LLMs
Discover Artificial IntelligenceThe central role of local LLMs is not merely to approximate cloud models at a smaller scale, but also to provide a practical user-side implementation of persistent adaptation that is difficult to support universally within shared cloud services.
Kei Itoh
doaj +1 more source
When Do LLMs Need Retrieval Augmentation? Mitigating LLMs' Overconfidence Helps Retrieval Augmentation [PDF]
Large Language Models (LLMs) have been found to have difficulty knowing they do not possess certain knowledge and tend to provide specious answers in such cases.
Ni, Shiyu +3 more
core
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
Advanced Intelligent Discovery, EarlyView.The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Advanced Intelligent Discovery, EarlyView.Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
Are LLMs Effective Backbones for Fine-tuning? An Experimental Investigation of Supervised LLMs on Chinese Short Text Matching [PDF]
The recent success of Large Language Models (LLMs) has garnered significant attention in both academia and industry. Prior research on LLMs has primarily focused on enhancing or leveraging their generalization capabilities in zero- and few-shot settings.
Liu, Hao +4 more
core
Advanced Intelligent Discovery, EarlyView.Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang +9 more
wiley +1 more source
Leveraging the True Depth of LLMs
The remarkable capabilities of Large Language Models (LLMs) are overshadowed by their immense computational cost. While recent work has shown that many LLM layers can be reordered or even removed with minimal impact on accuracy, these insights have not ...
Pagliardini, Matteo +4 more
core
Advanced Intelligent Discovery, EarlyView.An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin +4 more
wiley +1 more source
LLMs are not Tools, LLMs are Maybe-Tools
HOWL ARCHIVE PAPER - Registry ID: HOWL-INFO-8-2026. Dependencies: HOWL Foundation Only.
openaire +2 more sources