collaborators

11 papers

cs.CL2026

Beyond Captions: Context-Grounded Reconstruction for Biomedical Multimodal Continued Pretraining

Guanghao Zhu, Zeyu Liu, Zhitian Hou +10

Biomedical figures are explained not by captions alone but by body-text passages that discuss them. Yet current multimodal corpora typically reduce figures to isolated image-captio…

cs.LG2026

Access Sets Matter: Budgeting Expert Reads for Scalable Weight-Space Model Merging

Yuanyi Wang, Yanggan Gu, Su Lu +5

Weight-space model merging is usually formulated as an algebraic operation on checkpoints, yet at LLM scale the limiting resource is often the set of expert weights that must be re…

cs.CV2026

Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini

Madhuri Shanbhogue, Zhe Li, Shanfeng Zhang +86

We introduce Gemini Embedding 2, a native multimodal embedding model that allows embedding video, audio, image, and text modalities in a unified representation space. We leverage t…

cs.LG2026

Not All Disagreement Is Learnable: Token Teachability in On-Policy Distillation

Yuanyi Wang, Su Lu, Yanggan Gu +6

On-policy distillation (OPD) trains a student on its own rollouts with token-level teacher supervision. Recent selective OPD methods exploit the non-uniformity of OPD signals by pr…

cs.LG2026

InfiFPO: Implicit Model Fusion via Preference Optimization in Large Language Models

Yanggan Gu, Yuanyi Wang, Zhaoyi Yan +4

Model fusion combines multiple Large Language Models (LLMs) with different strengths into a more powerful, integrated model through lightweight training methods. Existing works on…

cs.CL2026

InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion

Yuanyi Wang, Zhaoyi Yan, Yiming Zhang +4

Recent advances in large language models (LLMs) have intensified efforts to fuse heterogeneous open-source models into a unified system that inherits their complementary strengths.…