Latent Thinking Optimization
Code for supervising and improving latent reasoning by treating hidden-state correctness signals as a latent reward model.
Reproducible benchmarks, research systems, and open-source implementations connected to our publications.
14 projects
Code for supervising and improving latent reasoning by treating hidden-state correctness signals as a latent reward model.
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.
The official implementation of a guided-calibration framework for denoising multimodal recommender systems.
A decoupled parameter-efficient adaptation framework for symmetric and asymmetric multimodal foundation models in recommendation.
A conversational recommendation system that combines a learned agent with Monte Carlo tree search for multi-turn planning.
An open implementation for aligning language-model recommenders with both relevance and serendipity objectives.
A teacher-assisted Wasserstein distillation pipeline for compressing multimodal recommenders into efficient ID-based student models.
Uncertainty-aware knowledge tracing that represents student states as distributions instead of fixed deterministic embeddings.