WeightCLIP: Aligning Datasets and Models for Weight Space Learning
WeightCLIP learns dataset-aligned latent space for neural network weights using contrastive learning on model and dataset embeddings.
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WeightCLIP learns dataset-aligned latent space for neural network weights using contrastive learning on model and dataset embeddings.
Fuzzy logic extension of Answer Set Programming bridges vague qualitative reasoning with numerical data.
Systematic review of non-social-media datasets for mental health disorder detection via NLP and ML.
MentalThink equips multimodal LLMs with SVG-based visual reasoning for structured spatial problem-solving.
Selective prediction framework enables LLMs to abstain on uncertain inputs, balancing risk-coverage tradeoff.
GameEngineBench evaluates coding agents on C++ implementation tasks in Unreal Engine real-time environments.
Generator-fixer self-play with automatic curriculum scales code repair via RL without paired datasets.
Co-adaptive LoRA determines domain participation weights and multi-task grouping without labels via forward passes.
Theoretical analysis shows projected Adam with arbitrary moment decay exhibits non-zero average regret.
Mixture-of-Gaussians framework provides principled schedule design for Brownian Bridge Diffusion Models.
AGL-1 governance layer enforces authorization, audit, and agent constraints across distributed enterprise AI systems.
Two-stage retrieval system combining lightweight embeddings with expensive rankers for efficient candidate selection in similarity-based search.
AquaGen generates all-atom molecular configurations matching Boltzmann distributions faster than molecular dynamics simulations.
CAGE-1 benchmark evaluates enterprise agentic AI on authorization, policy compliance, tool safety, and memory validity in operational workflows.
Graph p-Laplacian solver for semi-supervised learning using continuation method to handle nonlinear energy minimization.
DeepSeek V3 and Kimi K2 perform structured reasoning over filler tokens with no visible output, revealing hidden computation interpretability challenges.
STRATOS framework bridges symbolic-numeric gap in Text-to-SQL querying for meteorological datasets via domain-specific engineering.
Comprehensive MI estimation benchmark suite using copula theory to evaluate estimators on high-dimensional, realistic distributions.
IVD-SSM state-space model for SemEval-2026 narrative similarity task isolating causal patterns without Transformer quadratic cost.
Multiple instance learning framework trains cancer pathology classifiers on patient-level labels without report-level annotations.
Controlled failure modes in language models trained with RL reveal distribution shift vulnerabilities and post-training generalization failures.
Clinical NLP task on TNM cancer staging using ClinicalBERT, BioBERT, and classical ML on TCGA pathology reports.
WorldBagel: unified multimodal framework for Vision-Language-Action-World modeling in robotic manipulation tasks.
ADP: adversarial dynamics priors for robust humanoid locomotion control via CoM and contact force regularization.
Best-of-Better-N: in-context learning method to improve inference-time LLM alignment via retrieved high-reward responses.
SkillOpt-Lite: minimal skill optimization pipeline for autonomous agents via zeroth-order optimization, grounded in Claude.
HiMe: hierarchical embodied memory framework decoupling Vision-Language-Action control into frequency-stratified executor and reasoning tiers.
TRIAGE: stage-aware evaluation framework for LLM-automated Graph-RAG systems, localizing failures in extraction and inference.
Continuous test-time training for LLM agents across multi-turn episodes, balancing adaptation with drift prevention.
Router-oracle gap decomposition: separating reproducible specialist advantage from single-draw label noise in LLM routing.