activity
20232026
most citedDYNA: Disease-Specific Language Model for Variant Pathogenicity

2 citations · 2 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Video2World: Benchmarking Coding Agents for Interactive World Modeling from Embodied Videos

Jinzhou Tang, Zijun Zhang, Jing Yang +10

Building interactive simulators from real-world observations is a promising way to scale embodied data, but current pipelines still rely heavily on manual environment construction…

cs.CV2026

CausalWM: Causal Chain-of-Thought Reasoning for Embodied World Model

Ziming Xu, Shuang Liang, Ruobing Han +10

Embodied world models learn to predict future physical dynamics from visual observations and control signals, where physical knowledge is implicitly entangled within latent represe…

cs.CV2026

Causally Debiased Latent Action Model for Embodied Action-Conditioned World Models

Yufan Wei, Kun Zhou, Lingjun Mao +9

Action-conditioned world models (ACWMs) aim to simulate future observations conditioned on embodied actions. However, learning controllable ACWMs requires large-scale action-labele…

cs.CV2025

Learning Plug-and-play Memory for Guiding Video Diffusion Models

Selena Song, Ziming Xu, Zijun Zhang +4

Diffusion Transformer(DiT) based video generation models have recently achieved impressive visual quality and temporal coherence, but they still frequently violate basic physical l…

cs.CL2025

Better Prompt Compression Without Multi-Layer Perceptrons

Edouardo Honig, Andrew Lizarraga, Zijun Frank Zhang +1

Prompt compression is a promising approach to speeding up language model inference without altering the generative model. Prior works compress prompts into smaller sequences of lea…

q-bio.CB2024

Long-range gene expression prediction with token alignment of large language model

Edouardo Honig, Huixin Zhan, Ying Nian Wu +1

Gene expression is a cellular process that plays a fundamental role in human phenotypical variations and diseases. Despite advances of deep learning models for gene expression pred…

q-bio.GN2024★ 2 cited

DYNA: Disease-Specific Language Model for Variant Pathogenicity

Huixin Zhan, Zijun Zhang

Clinical variant classification of pathogenic versus benign genetic variants remains a challenge in clinical genetics. Recently, the proposition of genomic foundation models has im…

q-bio.GN2024

Efficient and Scalable Fine-Tune of Language Models for Genome Understanding

Huixin Zhan, Ying Nian Wu, Zijun Zhang

Although DNA foundation models have advanced the understanding of genomes, they still face significant challenges in the limited scale and diversity of genomic data. This limitatio…

q-bio.GN2023

ProPath: Disease-Specific Protein Language Model for Variant Pathogenicity

Huixin Zhan, Zijun Zhang

Clinical variant classification of pathogenic versus benign genetic variants remains a pivotal challenge in clinical genetics. Recently, the proposition of protein language models…