Implement a reasoning LLM in PyTorch from scratch, step by step

Implementation of paper: Flux Already Knows – Activating Subject-Driven Image Generation without Training

[ICML 2026] Decoding Tree Sketching (DTS): a training-free & model agonistic & plug-in framework for LLM parallel reasoning.

Efficient Test-Time Scaling for Small Vision-Language Models, official implementation of the ICLR'26 paper, test-time scaling via test-time augmentation

The official implementation for paper "AdaExplore: Failure-Driven Adaptation and Diversity-Preserving Search for Efficient Kernel Generation"

[NeurIPS 2025] Inference-Time Text-to-Video Alignment with Diffusion Latent Beam Search

[CVPR2026 Findings] VHS: Verifier on Hidden States, an efficient inference-time scaling verification framework for DiT-based image generation.

[COLM 2025] Adaptive Skill-based In-context Math Instruction for Small Language Models

[arXiv'26] LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion

Experiments on System 2 reasoning — neuro-symbolic learning, inference-time scaling, LLM agents, RL post-training in LLMs, and Graph-based retrieval.

Code for "Challenges in Inference Time Scaling with Uncertainty Aware Tree Search" @ ICLR 26 Workshops

Empirical study of latent quality in LLMs under critical engagement