From the 1 of 7 linked papers with an AI index.
7 papers
DynEval: Holistic Evaluations of T2I Generative Models in the Wild
Shyam Marjit, Dheeraj Baiju, Anuj Shikarkhane +3
The paper introduces DynEval, a dynamic evaluation framework that jointly assesses text-to-image alignment and image quality for T2I models, using large synthetic datasets and a di…
Flash-BoN: Instant Drafts for Inference-Time Scaling in Diffusion Models
Ruchit Rawal, Reza Shirkavand, Sayak Paul +5
Inference-time scaling for text-to-image generation has progressed from simple Best-of- (BoN) sampling to guided search methods that verify and steer candidate trajectories at i…
TAROT: Test-driven and Capability-adaptive Curriculum Reinforcement Fine-tuning for Code Generation with Large Language Models
Chansung Park, Juyong Jiang, Fan Wang +4
Large Language Models (LLMs) are changing the coding paradigm, known as vibe coding, yet synthesizing algorithmically sophisticated and robust code still remains a critical challen…
Margin-aware Preference Optimization for Aligning Diffusion Models without Reference
Jiwoo Hong, Sayak Paul, Noah Lee +3
Modern preference alignment methods, such as DPO, rely on divergence regularization to a reference model for training stability-but this creates a fundamental problem we call "refe…
SANA-Sprint: One-Step Diffusion with Continuous-Time Consistency Distillation
Junsong Chen, Shuchen Xue, Yuyang Zhao +6
This paper presents SANA-Sprint, an efficient diffusion model for ultra-fast text-to-image (T2I) generation. SANA-Sprint is built on a pre-trained foundation model and augmented wi…
LlamaDuo: LLMOps Pipeline for Seamless Migration from Service LLMs to Small-Scale Local LLMs
Chansung Park, Juyong Jiang, Fan Wang +2
The widespread adoption of cloud-based proprietary large language models (LLMs) has introduced significant challenges, including operational dependencies, privacy concerns, and the…