activity
20242026
most citedAdaptive Length Image Tokenization via Recurrent Allocation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

EpiCon: Collective Agent Learning through Co-Evolving Multimodal Memory

Ziyun Zeng, Hang Hua, Shaden Alshammari +3

Agents can learn from past executions, but enabling different agents to reuse and build on one another's experience remains challenging. We introduce EpiCon, a shared multimodal me…

cs.AI2026

MathNet: a Global Multimodal Benchmark for Mathematical Reasoning and Retrieval

Shaden Alshammari, Kevin Wen, Abrar Zainal +5

Mathematical problem solving remains a challenging test of reasoning for large language and multimodal models, yet existing benchmarks are limited in size, language coverage, and t…

cs.CV2026

End-to-End Training for Unified Tokenization and Latent Denoising

Shivam Duggal, Xingjian Bai, Zongze Wu +5

Latent diffusion models (LDMs) enable high-fidelity synthesis by operating in learned latent spaces. However, training state-of-the-art LDMs requires complex staging: a tokenizer m…

cs.CV2025

Single-pass Adaptive Image Tokenization for Minimum Program Search

Shivam Duggal, Sanghyun Byun, William T. Freeman +2

According to Algorithmic Information Theory (AIT) -- Intelligent representations compress data into the shortest possible program that can reconstruct its content, exhibiting low K…

cs.CV2025

Eval3D: Interpretable and Fine-grained Evaluation for 3D Generation

Shivam Duggal, Yushi Hu, Oscar Michel +7

Despite the unprecedented progress in the field of 3D generation, current systems still often fail to produce high-quality 3D assets that are visually appealing and geometrically a…

cs.CV2024★ 1 cited

Adaptive Length Image Tokenization via Recurrent Allocation

Shivam Duggal, Phillip Isola, Antonio Torralba +1

Current vision systems typically assign fixed-length representations to images, regardless of the information content. This contrasts with human intelligence - and even large langu…