42 citations · 52 across the 15 of their papers we have counts for
17 papers
Primal Generation, Dual Judgment: Self-Training from Test-Time Scaling
Yizhu Jiao, Ruixiang Zhang, Richard Bai +3
Code generation is typically trained in the primal space of programs: a model produces a candidate solution and receives sparse execution feedback, often a single pass/fail bit. Te…
Embarrassingly Simple Self-Distillation Improves Code Generation
Ruixiang Zhang, Richard He Bai, Huangjie Zheng +3
Can a large language model (LLM) improve at code generation using only its own raw outputs, without a verifier, a teacher model, or reinforcement learning? We answer in the affirma…
Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling
Huangjie Zheng, Shansan Gong, Ruixiang Zhang +5
Standard discrete diffusion models treat all unobserved states identically by mapping them to an absorbing [MASK] token. This creates an 'information void' where semantic informati…
ChipChat: Low-Latency Cascaded Conversational Agent in MLX
Tatiana Likhomanenko, Richard He Bai, Zijin Gu +8
The emergence of large language models (LLMs) has transformed spoken dialog systems, yet the optimal architecture for real-time on-device voice agents remains an open question. Whi…
Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows
Ruixiang Zhang, Shuangfei Zhai, Jiatao Gu +6
Autoregressive models have driven remarkable progress in language modeling. Their foundational reliance on discrete tokens, unidirectional context, and single-pass decoding, while…
DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
Shansan Gong, Ruixiang Zhang, Huangjie Zheng +4
Diffusion large language models (dLLMs) are compelling alternatives to autoregressive (AR) models because their denoising models operate over the entire sequence. The global planni…
STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
Jiatao Gu, Tianrong Chen, David Berthelot +7
We present STARFlow, a scalable generative model based on normalizing flows that achieves strong performance in high-resolution image synthesis. The core of STARFlow is Transformer…
Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion
Ruixiang Zhang, Shuangfei Zhai, Yizhe Zhang +4
Discrete diffusion is a promising framework for modeling and generating discrete data. In this work, we present Target Concrete Score Matching (TCSM), a novel and versatile objecti…
Composition and Control with Distilled Energy Diffusion Models and Sequential Monte Carlo
James Thornton, Louis Bethune, Ruixiang Zhang +3
Diffusion models may be formulated as a time-indexed sequence of energy-based models, where the score corresponds to the negative gradient of an energy function. As opposed to lear…
What Makes the Preferred Thinking Direction for LLMs in Multiple-choice Questions?
Yizhe Zhang, Richard Bai, Zijin Gu +5
Language models usually use left-to-right (L2R) autoregressive factorization. However, L2R factorization may not always be the best inductive bias. Therefore, we investigate whethe…
Normalizing Flows are Capable Generative Models
Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran +7
Normalizing Flows (NFs) are likelihood-based models for continuous inputs. They have demonstrated promising results on both density estimation and generative modeling tasks, but ha…
TypeScore: A Text Fidelity Metric for Text-to-Image Generative Models
Georgia Gabriela Sampaio, Ruixiang Zhang, Shuangfei Zhai +4
Evaluating text-to-image generative models remains a challenge, despite the remarkable progress being made in their overall performances. While existing metrics like CLIPScore work…
dMel: Speech Tokenization made Simple
Richard He Bai, Tatiana Likhomanenko, Ruixiang Zhang +3
Large language models have revolutionized natural language processing by leveraging self-supervised pretraining on vast textual data. Inspired by this success, researchers have inv…
Improving GFlowNets for Text-to-Image Diffusion Alignment
Dinghuai Zhang, Yizhe Zhang, Jiatao Gu +4
Diffusion models have become the de-facto approach for generating visual data, which are trained to match the distribution of the training dataset. In addition, we also want to con…
How Far Are We from Intelligent Visual Deductive Reasoning?
Yizhe Zhang, He Bai, Ruixiang Zhang +4
Vision-Language Models (VLMs) have recently demonstrated incredible strides on diverse vision language tasks. We dig into vision-based deductive reasoning, a more sophisticated but…
Learning Representation from Neural Fisher Kernel with Low-rank Approximation
Ruixiang Zhang, Shuangfei Zhai, Etai Littwin +1
In this paper, we study the representation of neural networks from the view of kernels. We first define the Neural Fisher Kernel (NFK), which is the Fisher Kernel applied to neural…
An Attention Free Transformer
Shuangfei Zhai, Walter Talbott, Nitish Srivastava +4
We introduce Attention Free Transformer (AFT), an efficient variant of Transformers that eliminates the need for dot product self attention. In an AFT layer, the key and value are…