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Zhelun Shi

7 accepted papers

2026

OmniScale: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo

AAAI 2026technical

Recent advances in large language models (LLMs) have driven impressive progress in omni-modal understanding and generation. However, training omni-modal LLMs remains a significant challenge due to the heterogeneous model architectures required to process diverse modalities, necessitating sophisticat

Cited by 0SourcePDFScholar
2025

Chain-of-Imagination for Reliable Instruction Following in Decision Making

IROS 2025

Enabling the embodied agent to imagine step-by-step the future states and sequentially approach these situation-aware states can enhance its capability to make reliable action decisions from textual instructions. In this work, we introduce a simple but effective mechanism called Chain-of-Imagination

Cited by 0SourceScholar
2025

RH20T-P: A Primitive-Level Robotic Manipulation Dataset towards Composable Generalization Agents in Real-world Scenarios

IROS 2025

Achieving generalizability in solving out-of-distribution tasks is one of the ultimate goals of learning robotic manipulation. Recent progress of Vision-Language Models (VLMs) has shown that VLM-based task planners can alleviate the difficulty of solving novel tasks, by decomposing the compounded ta

Cited by 1SourceScholar
2025

Systematic Reward Gap Optimization for Mitigating VLM Hallucinations

NeurIPS 2025poster

The success of Direct Preference Optimization (DPO) in mitigating hallucinations in Vision Language Models (VLMs) critically hinges on the true reward gaps within preference pairs. However, current methods, typically relying on ranking or rewriting strategies, often struggle to optimize these reward…

Cited by 0SourceScholar
2025

T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation

CVPR 2025poster

Text-to-image (T2I) models have rapidly advanced, enabling the generation of high-quality images from text prompts across various domains. However, these models present notable safety concerns, including the risk of generating harmful, biased, or private content. Current research on assessing T2I s…

2025

WorldSimBench: Towards Video Generation Models as World Simulators

ICML 2025poster

Recent advancements in predictive models have demonstrated exceptional capabilities in predicting the future state of objects and scenes. However, the lack of categorization based on inherent characteristics continues to hinder the progress of predictive model development. Additionally, existing ben…

Cited by 18SourcePDFScholar
2023

LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark

NeurIPS 2023poster

Large language models have emerged as a promising approach towards achieving general-purpose AI agents. The thriving open-source LLM community has greatly accelerated the development of agents that support human-machine dialogue interaction through natural language processing. However, human interac…