Generative Chemical Language Models for Energetic Materials Discovery
Generative molecular language models pre-trained on chemical data and fine-tuned for energetic materials discovery.
Generative molecular language models pre-trained on chemical data and fine-tuned for energetic materials discovery.
Proposes automated discovery approach for computer architecture design using AI, addressing post-Moore's Law era challenges.
TensorBoard plugin for interactive multi-metric visualization and fairness analysis during ML model training.
Multimodal violence detection model combining VideoMamba and AudioMamba with conditional LoRA steering.
Causality mining approach for diagnosing connected vehicle system failures in distributed cloud/edge infrastructure.
Addresses iterative image quality degradation in multi-turn editing with agentic systems using multi-modal models.
Diffusion policy approach with Bayesian expert selection for active multi-target tracking balancing exploration and exploitation.
Zero-shot quantization technique using weight-space arithmetic to transfer quantization robustness between models without training data.
Inference optimization method for frozen vision transformers through circuit duplication for marine species classification.
Study comparing RAG-based approach with traditional methods for Agile story point estimation in sprint planning.
Photoshop plugin using diffusion models for AI-assisted facial expression editing in stylized artwork without image degradation.
Lightweight query routing classifier for selecting optimal retrieval strategies in RAG pipelines based on query characteristics.
Machine learning model with physics constraints for climate downscaling using flow matching architecture.
Quantum computing approach using recurrent quantum circuits as reservoirs for temporal data processing.
Wearable AI agent on smart glasses enabling continuous perception and speech-driven task execution with OpenClaw agentic framework.
Statistical method for causal inference using regression discontinuity design in healthcare applications with survival outcomes.
Method using sparse autoencoders to discover language-specific features from monolingual data for controlling LLM output language without parallel data.
Discrete diffusion language model using tree-structured token prediction to reduce parameters and memory in language generation.
Video diffusion transformer framework for synthesizing diverse bimanual robot manipulation demonstrations from limited real data.
Framework combining score-based diffusion models as priors in plug-and-play optimization for imaging inverse problems.
Method for LLMs to dynamically compress intermediate reasoning thoughts into compact representations while maintaining reasoning quality.
Graph learning approach for melanoma detection in medical images using graph signal processing.
Framework for injecting bit-flip faults into DNNs used in autonomous driving systems to identify critical failure points.
Deep reinforcement learning framework for optimizing land-use allocation in Lake Malawi Basin to maximize ecosystem service value.
Debiased machine learning approach for conformal prediction of counterfactual outcomes under confounding.
Theoretical analysis of Sinkhorn-Knopp algorithm efficiency for entropically regularized optimal transport.
Method using Rényi attention entropy for patch pruning in transformers to reduce quadratic self-attention cost.
Theoretical analysis reconciling practitioner and statistician perspectives on Elo ranking algorithms.
Study on adversarial attacks against transformer-based malware detectors using control flow graphs, examining robustness of RoBERTa models.
SecureAFL: Asynchronous federated learning framework addressing straggler problem while maintaining security.
Study comparing LLM probed representations with performance on narrative analogical reasoning tasks.
PhaseFlow4D: Latent diffusion for 4D particle beam reconstruction from sparse 2D projections with physical constraints.
Machine learning attacks on Learning with Errors problem using data repetition and stepwise regression.
Secure-by-design GenAI framework integrating PromptShield for LLM-based cloud security and forensic analysis.
Fused multinomial logistic regression leveraging summary-level external machine-learning predictions for data integration.
Cross-Modal Graphical Lasso for learning interpretable multimodal representations by disentangling shared and specific topologies.
Value-based safety forecasting for streaming LLM outputs, improving response moderation on partial generations.
Fixed-confidence best arm identification in semiparametric bandits with instance-optimal sample complexity bounds.
Computer vision method addressing object occlusion through pattern masking and severity-informed classification.
Causal graph-attention approach to detect and mitigate hallucinations in LLMs for improved factual reliability.
Jellyfish: Zero-shot federated unlearning scheme using knowledge disentanglement for privacy-preserving federated learning.
Study on connectome-constrained neural networks and biological graph topology effects on learning efficiency.
TORA: Topology-first framework for 3D shape assembly using flow-matching and pretrained 3D encoders.
Fault detection framework for hybrid dynamical systems combining Petri nets with semi-supervised anomaly detection.
FactReview: LLM-based peer review system that grounds claims in evidence from papers, related work, and code to improve ML paper reviewing.
Real-time traffic monitoring system using YOLOv11 object detection and multi-object tracking in PyTorch/OpenCV.
Fine-tuned language models enhance embeddings for cognitive diagnosis in online education systems by incorporating semantic representations.
Event camera and neuromorphic hardware approach for efficient spacecraft pose estimation during autonomous rendezvous operations in space.
Comparison of CNN and CNN-Transformer models for robust speech recognition from MEG brain signals under distribution shift using LibriBrain benchmark.
Mathematical framework for primal-dual optimization methods handling nonsmooth nonconvex problems with orthogonality constraints on Stiefel manifolds.