LLMPopcorn
An LLM-assisted pipeline for generating and evaluating titles, cover prompts, and short-video prompts designed for audience appeal.
Reproducible benchmarks, research systems, and open-source implementations connected to our publications.
Browse by research area →9 projects
An LLM-assisted pipeline for generating and evaluating titles, cover prompts, and short-video prompts designed for audience appeal.
The official implementation of a meta-learning framework that bridges next-item prediction and masked-language modeling for recommendation.
A benchmark for measuring how multimodal language models reconstruct missing product text or imagery and support recommendation.
A simulation-and-real-world benchmark for testing physical reasoning and prediction in vision-language and world models.
Skill-centered assessment for agent skills across utility, efficiency and cost, and safety, backed by sandboxed execution evidence.
An adaptive meta-balancing framework for integrating heterogeneous graph signals in knowledge tracing.
Frequency-decoupled knowledge distillation for reducing multimodal recommendation cost while preserving useful cross-modal signals.
A decoupled parameter-efficient adaptation framework for symmetric and asymmetric multimodal foundation models in recommendation.
An open implementation for aligning language-model recommenders with both relevance and serendipity objectives.