TAUE: Training-free Noise Transplant and Cultivation Diffusion Model
Training-free diffusion model enhancement for multi-layer text-to-image generation without fine-tuning.
Training-free diffusion model enhancement for multi-layer text-to-image generation without fine-tuning.
Graph-based retrieval-augmented generation system addressing hallucination, reasoning transparency, and answer quality for LLMs.
Large-scale underwater segmentation dataset and open-vocabulary segmentation models for marine organism recognition.
Deep learning method for geometric representation learning on Grassmannian manifolds using multi-subspace fusion.
Federated learning approach addressing data distribution shifts using causal inference for out-of-distribution robustness.
Method for steering LLM behavior through activation injection to enhance empathy and negotiation capabilities using attribution patching.
Research on masked auto-regressive diffusion models optimizing inference speed for reinforcement learning applications through architectural improvements.
PRISM complex-valued encoder with phase-based spectral filtering shows semantic relationships correlate with phase angles in neural sequence models.
DiG differential grounding proxy task enhances fine-grained visual perception in MLLMs by learning differences between image pairs for precise spatial reasoning.
DexWM world model predicts latent environmental states for fine-grained dexterous hand-object interactions from human videos.
Programming abstraction for shared state between prompts and programs, enabling interoperability between natural language and traditional programming with LLMs.
AI4EOSC federated cloud platform for AI in scientific research with reproducible ML lifecycle management across distributed e-Infrastructures.
SentGraph hierarchical sentence graph enables multi-hop retrieval-augmented generation by constructing coherent evidence chains from multiple documents for complex QA.
Audits political alignment in 26 LLMs using psychometric inventories and news bias labeling across prompt variants to evaluate behavioral bias.
Vision-language reasoning for urban socio-semantic segmentation from satellite imagery, distinguishing socially-defined categories beyond physical attributes.
Ablates RLVR pipeline components for code verifiers: intermediate thinking traces, negative samples, and on-policy training to reduce adoption cost barriers.
CFM language-aligned concept foundation model decomposes vision model representations into human-interpretable concepts with spatial grounding for diverse downstream tasks.
LREAD rubric-based framework with three-phase expert study calibrates human detection of LLM-generated Korean text to improve attribution accuracy beyond surface-level assessment.
Time-annealed perturbation sampling for diffusion language models enables diverse generation across semantic and reasoning paths by controlling temporal denoising.
Bauplan code-first lakehouse with data contracts, versioning, and transactional pipelines for concurrent AI/analytics workloads supporting both human and agent workflows.
Predicts LLM success from pre-generation internal activations using linear probes to enable efficient inference routing on math and coding tasks.
Benchmark evaluating multimodal LLMs' ability to understand pedagogical reasoning and science instruction in K-12 classroom videos with model-based explanations.
Descent-guided policy gradient method addresses cross-agent noise scaling in multi-agent reinforcement learning, improving sample complexity from O(N/ε) to sublinear bounds.
KEEP system optimizes KV-cache memory management for memory-augmented LLMs in embodied planning, reducing prompt length and prefill latency for long-horizon tasks.
Experimental study of sycophancy in LLMs—tendency to favor user-affirming over critical responses—with controlled interventions to identify and prevent the alignment failure.
Proposes evolutionary algorithm for automated skull-face overlay alignment in forensic craniofacial superimposition analysis.
Evaluates 5 open-source small LLMs (Gemma, Phi, Llama, Mistral, Meditron) for clinical QA reliability and prompt sensitivity in low-resource healthcare settings.
DCDP: Dynamic closed-loop diffusion policy framework with real-time correction for robotic manipulation in dynamic scenarios.
AOI: Trainable multi-agent LLM framework for autonomous cloud diagnosis and SRE automation learning from failed trajectories.
SWE-CI: Benchmark evaluating LLM agent capabilities in continuous integration for long-term codebase maintenance and feature iterations.
Optimizes KV cache in transformers by reducing key dimensionality to log(N) while preserving value information for efficiency.
CRIMSON: Clinically-grounded LLM metric for evaluating chest X-ray report generation on diagnostic correctness and patient safety.
Systematic framework defining boundaries between AI models and AI systems for regulatory and policy compliance purposes.
Amnesia: Adversarial semantic activation steering technique for controlling harmful content generation in large language models.
DUCTILE: Agentic LLM orchestration framework for automating engineering analysis and tool coordination in product development.
Human-LLM collaboration quantifying Collatz conjecture dynamics using exact arithmetic and probabilistic analysis.
ELISA: Interpretable AI agent combining scGPT embeddings with BioBERT for expression-grounded discovery in single-cell genomics.
FRAME: Systematic framework for real-world AI evaluation generating contextual evidence on model behavior in organizational environments.
Hypergraph-based pre-training for atrial fibrillation prediction in ESUS patients using machine learning on high-dimensional medical data.
SHAMISA: Self-supervised no-reference image quality assessment using non-contrastive learning on unlabeled distorted images.
Study evaluating human perception and sensitivity to synthetic deepfake videos for disinformation research.
APEX-Searcher: LLM agent with agentic planning for multi-hop retrieval-augmented generation to enhance complex question answering.
Audio-visual speech enhancement using RL with LLM-based interpretable reward model for perceptual quality optimization.
AI-ECG system (Pocket-K) for non-invasive hyperkalemia detection using ECGFounder foundation model for clinical deployment.
Two-stage video dubbing system using discrete flow matching for synchronized speech synthesis and cross-modal alignment.
Neural compression framework using SIREN auto-decoders for seismic velocity models from OpenFWI benchmark.
arXiv: Geometric data augmentation preserving ring-type polygon topology for architectural floorplan analysis segmentation.
arXiv: Two-stage multimodal approach combining weather foundation models with satellite data for solar irradiance forecasting.
arXiv: Post-hoc model-agnostic explanation method using perturbation selection for uncertainty-aware surrogate model approximations.
arXiv: Analyzes error sources in global feature effect estimation (PD, ALE plots) for black-box model interpretation.