All Articles
17327 articles total
Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis
A large-scale study analyzing the usage patterns of the Syntea AI learning assistant among over 77,000 higher education students.
Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation
Presentation of IG-Bench, a benchmark designed to test if LLMs can reason about the lineage and evolutionary history of scientific ideas.
Towards the Explainability of Temporal Graph Networks via Memory Backtracking and Topological Attribution
A new method for explaining Temporal Graph Network (TGN) predictions using memory backtracking and topological attribution.
LLT: Local Linear Transformer for PDE Operator Learning
Introduction of the Local Linear Transformer (LLT), which improves efficiency and accuracy for solving Partial Differential Equations (PDEs).
ReCoLoRA: Spectrum-Aware Recursive Consolidation for Continual LLM Fine-Tuning
ReCoLoRA, a spectrum-aware recursive consolidation framework for continual fine-tuning of LLMs to prevent catastrophic forgetting.
Omni-Sleep: A Sleep Foundation Model via Hierarchical Contrastive Learning of CNS--ANS Dynamic
Omni-Sleep, a foundation model for sleep physiology that utilizes hierarchical contrastive learning of CNS-ANS dynamics.
Applying JEPA-Style Predictive Learning to JA4-Derived Network Fingerprints
Researchers developed JA4-JEPA, a Transformer-based model that uses JEPA-style predictive learning to create useful embeddings from JA4 network fingerprints for protocol-family classification.
Drift-Aware Temporal Graph Rewiring (DATGR) for Adaptive Semantic Modeling in Biomedical Text
The DATGR framework introduces a drift-aware temporal graph rewiring method to update semantic models in biomedical text, improving link-prediction recall without retraining embeddings.
AI-guided stimuli discovery and generation to optimize facial emotion perception studies in autism
A new model-guided framework uses AI to discover and generate stimuli that maximize behavioral differences in facial emotion perception studies for autistic individuals.
CommuniWave:A Machine Learning Model for Quantifying the Degree of Temporary Informal Behavior in Urban Communities
CommuniWave is a machine learning model that quantifies informal behavior in urban communities using a combination of BCN, a custom YOLOv10 variant (YLX), and random forests.
SHAP-Weighted Cross-Modal Expert Fusion for Emotion and Sentiment Recognition: Evidence and Limits
This paper analyzes XAI-guided adaptive fusion for multimodal emotion recognition, finding that sum-abs SHAP reduction effectively preserves attribution for high-dimensional cross-modal experts.
Towards Precision Therapy in Hepatocellular Carcinoma: A Clinical-Reasoning LLM for Risk Stratification and Treatment Guidance
HCC-STAR is a clinically aligned LLM for hepatocellular carcinoma risk stratification and treatment guidance, showing superior performance over existing guidelines and other LLMs in multi-center tests.
The complexities of patient-centred conversational artificial intelligence
Researchers developed a patient simulator to model diverse communication styles in health chatbots, highlighting how communication diversity affects triage outcomes in LLMs.
Formal Mechanisms for Market Stability in Self-Interested Agent Societies: A Marketplace Simulation Study
A simulation study using DeepSeek-V3 agents found that a 'Mediation' mechanism provides stability and adversarial robustness in self-interested agent marketplaces.
SolarChain-Eval: A Physics-Constrained Benchmark for Trustworthy Economic Agents in Decentralized Energy Markets
SolarChain-Eval is a physics-constrained benchmark for evaluating the trustworthiness and safety of autonomous economic agents in decentralized energy markets.
Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents
The Proactive Memory Agent is a plug-and-play module that actively injects decision-relevant reminders into long-horizon agent trajectories to prevent behavioral state decay.
MobiDiff: Semantic-Aware Multi-Channel Discrete Diffusion for Human Mobility Data Generation
MobiDiff is a discrete diffusion framework designed for efficient and privacy-preserving human mobility data generation by denoising multi-channel semantic skeletons.
FedOPAL: One-Shot Federated Learning via Analytic Visual Prompt Tuning
FedOPAL introduces a one-shot federated learning framework using analytic visual prompt tuning to handle heterogeneous data on the edge with zero server-side training costs.
Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning
Research into the 'Knowing--Using Gap' in LLMs reveals that memorized knowledge often fails to generalize because it is not routed to computation-effective layers.
Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination
G-Frame is a multi-agent framework using game theory to reduce LLM hallucinations in scientific domains, leading to the creation of the OmniChem model for chemistry.