Compiled AI: Deterministic Code Generation for LLM-Based Workflow Automation
Compiled AI: Paradigm where LLMs generate executable code during compilation for deterministic, model-free workflow automation execution.
Compiled AI: Paradigm where LLMs generate executable code during compilation for deterministic, model-free workflow automation execution.
Planning to Explore: Curiosity-driven planning approach for LLM-based test generation using Bayesian principles to reach deep code branches.
Analysis of 10 proposed measures for evaluating qualitative interview response quality to determine predictive validity.
Adaptive Thinking Budgets: Method for allocating inference-time compute efficiently across multi-turn LLM reasoning based on turn difficulty.
Modality-aware vector-quantized VAE for reconstructing multimodal brain MRI data across different imaging modalities.
Large Sparse Reconstruction Model studies scaling transformer context windows for improved 3D object reconstruction from multiple views.
OrthoFuse: Training-free method for merging multiple adapters in diffusion models using Riemannian geometry.
Study comparing encoder and decoder-based LLMs for screening clinical narratives to automate patient recruitment for clinical trials.
RoboPlayground: Framework for democratizing robotic manipulation evaluation through structured physical domain benchmarks.
Optimization strategies using curvature-aware methods to improve convergence speed and accuracy of physics-informed neural networks.
XMark: Multi-bit watermarking method for embedding imperceptible messages in LLM-generated text for attribution and tracing.
Study on how transformer language models learn second-order generalizations about object categories from synthetic data.
Temporal extension of TabDDPM for time-series data generation, addressing temporal dependencies in diffusion-based synthetic data creation.
Region-based re-ranker for multi-modal RAG reducing visual distractors by formulating region selection as decision-making problem.
Multi-agent spec-driven development pipeline with context-grounding hooks to prevent hallucinations and architectural violations in LLM coding agents.
Formal verification of security vulnerabilities in AI-generated code across 7 frontier LLMs and 500 prompts using Z3 SMT solver.
Study on training LLMs to express uncertainty explicitly as control interface for abstention and verification tasks.
Novel autoregressive paradigm for long-sequence symbolic music generation using anchored cyclic generation.
Diagnostic RAG system for IT support with explicit diagnostic state tracking across turns to accumulate evidence and resolve hypotheses.
Multi-agent LLM system for clinician-in-the-loop gait analysis report drafting, coordinating specialized agents for multimodal data synthesis.
Training-free quantization method for 3D reconstruction models using random rotations without per-scene fine-tuning.
Study on AI's role in collective decision-making systems and procedural legitimacy conditions for participants.
Long video understanding via spatio-temporally structured intent-aware RAG, preserving video structure while retrieving query-relevant evidence.
System for adaptive LoRA hyperparameter tuning and orchestration across heterogeneous multi-tenant LLM fine-tuning workloads.
Open-source digital twin simulator integrating natural language with renewable energy microgrid dynamics and dataset.
Security study of data exfiltration attacks via backdoored tool-use LLM agents, presenting Back-Reveal attack with semantic triggers.
3D human reconstruction from single images in multi-person scenes with interaction awareness.
Open-source governance-aware agentic platform for security operations, addressing alert fatigue and cross-source event correlation with LLM assistance.
Vision-language reward model framework dynamically decomposing evaluation into interpretable dimensions via gating mechanism.
Multi-agent RAG framework using agents for IoT network intrusion detection with experience library, improving interpretability over ML approaches.
Statistical framework treating LLM evaluation as tensor completion problem, addressing uncertainty quantification in pairwise comparison leaderboards.
Empirical study on fault localization's role in LLM-based automated program repair, evaluating context requirements across 500 SWE-bench instances.
Diagnostic framework combining vision-language models with flow matching and spectral detection for veterinary pneumothorax diagnosis.
Learned elevation models as alternative to LiDAR for radio environment map estimation in wireless networks.
Singing voice conversion system using boundary-aware information bottleneck for fine-grained style control.
Analysis of transformer embedding trajectories exhibiting turbulence-like 5/3 power-law spectral scaling across languages.
FastDiSS improves few-step diffusion language models for sequence-to-sequence generation by addressing self-conditioning approximation gaps.
Context-Agent framework using dynamic discourse trees for hierarchical non-linear dialogue management in LLMs.
Empirical forensic analysis of OpenClaw agentic AI system, examining internal state reconstruction and action logging for digital investigations.
Modular platform combining speech recognition, translation, emotion classification, and sign language rendering using open-source AI services.
Extended reality framework integrating AI services for sign language interpretation and emotion recognition in video conferencing.
Study evaluating style transfer randomization for domain generalization in computer vision synthetic-to-real transfer.
Multimodal model for medical image segmentation guided by clinical text using semantic-topological graph reasoning.
Foundation model for gastrointestinal endoscopy diagnosis using analogical reasoning to improve generalizability and robustness.
Physics-informed neural networks for modeling multiscale fluid dynamics with long-range dependencies in Navier-Stokes equations.
Research characterizing LLM chain-of-thought reasoning as trajectories through representation space, showing step-specific subspaces become more separable with layer depth.
SnapFlow self-distillation method converting 10-step flow-matching VLA models to one-step action generation for real-time robotic manipulation.
Rectified Schrödinger Bridge matching approach for few-step visual navigation in embodied AI agents reducing denoising iterations.
Multimodal LLM-based security assessment method for cyber-physical systems with incomplete architectural documentation and legacy systems.
Framework for converting attention mechanisms between architectures (MLA, SWA) to reduce KV cache memory and bandwidth in LLM inference.