Implementation of paper: Flux Already Knows – Activating Subject-Driven Image Generation without Training
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Updated
Sep 10, 2025 - Python
Implementation of paper: Flux Already Knows – Activating Subject-Driven Image Generation without Training
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 paper, test-time scaling via test-time augmentation
[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
The official implementation for paper "AdaExplore: Failure-Driven Adaptation and Diversity-Preserving Search for Efficient Kernel Generation"
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
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