From the 1 of 12 linked papers with an AI index.
12 papers
XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling
Jinxiu Liu, Xuanming Liu, Kangfu Mei +2
High-fidelity image generation faces a trade-off between speed and quality. Diffusion models produce strong visuals but require costly iterative sampling. Existing efficient method…
Open-Linguistic Concept Unified Learning for Cross-Site Interpretable Dermatology Image Diagnosis
Chengyu Wu, Junpeng Tan, Wanxiang Luo +3
Human-interpretable computer-aided diagnosis is crucial for clinical decision making. Concept-based models excel by providing transparent reasoning and enabling post-hoc, clinician…
SymbOmni: Evolving Agentic Omni Models via Symbolic Concept Learning
Jinxiu Liu, Jianru Li, Tanqing Kuang +4
The paper introduces SymbOmni, an agentic omni-model for visual generation that uses a symbolic concept memory to continuously learn and compose reusable instructions, enabling con…
Beyond the Sampled Token: Preserving Candidate Support in RLVR
Ruotian Peng, Yi Ren, Zhouliang Yu +2
We revisit exploration collapse in reinforcement learning with verifiable rewards (RLVR), from the perspective of the \emph{candidate distribution} for next-token prediction. We fo…
Drifting Preference Optimization for One-Step Generative Models
Zhou Jiang, Yandong Wen, Zhen Liu
One-step text-to-image generators are attractive for deployment because they generate an image with a single forward pass, but preference finetuning them remains difficult: standar…
PEFT-Arena: Understanding Parameter-Efficient Finetuning from a Stability-Plasticity Perspective
Yangyi Huang, Ruotian Peng, Zeju Qiu +4
Parameter-efficient finetuning (PEFT) has become the standard approach for adapting large language models, yet evaluations largely emphasize downstream accuracy while overlooking t…