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Letian Li

8 accepted papers

2026

CG-MLLM: Captioning and Generating 3D content via Multi-modal Large Language Models

ICML 2026poster

Large Language Models(LLMs) have revolutionized text generation and multimodal perception, but their capabilities in 3D content generation remain underexplored. Existing methods compromise by producing either low-resolution meshes or coarse structural proxies, failing to capture fine-grained geometr…

Cited by 0SourceScholar
2026

Disturbance-Robust Dynamical System Learning With Neural ODEs and Flow-Matching Augmentation

RA-L 2026

Autonomous dynamical systems (DS) are essential for imitation learning but often face challenges in simultaneously achieving high accuracy, stability guarantees, and resistance to disturbances. To overcome these limitations, this paper proposes a globally stable DS with trajectory attraction and dis

Cited by 0SourceScholar
2026

Fabric Dynamic Motion Modeling and Collision Avoidance with Oriented Bounding Box

ICRA 2026poster

Avoiding collision between the fabric and the obstacle is critical to transport fabric piece in the garment factory. If the fabric collides with the sharp-edged obstacle, it can be scratched or contaminated, resulting in poor product quality and increased waste. However, when we consider the fabric …

Cited by 0Scholar
2026

IGen: Scalable Data Generation for Robot Learning from Open-World Images

CVPR 2026

The rise of generalist robotic policies has created an exponential demand for large-scale training data. However, on-robot data collection is labor-intensive and often limited to specific environments. In contrast, open-world images capture a vast diversity of real-world scenes that naturally align

Cited by 0SourceScholar
2026

Position: Multi-Agent Systems Should Prioritize Concurrency Control

ICML 2026poster

LLM-based multi-agent systems (MAS) promise scalable collaboration, yet adding agents often *reduces* reliability. This position paper argues that many MAS failures are fundamentally **concurrency control problems**: agents concurrently read and write shared state, and long LLM inference windows amp…

Cited by 0SourceScholar
2026

Towards Self-Robust LLMs: Intrinsic Prompt Noise Resistance via CoIPO

ICLR 2026poster

Large language models (LLMs) have demonstrated remarkable and steadily improving performance across a wide range of tasks. However, LLM performance may be highly sensitive to prompt variations especially in scenarios with limited openness or strict output formatting requirements, indicating insuffic…

Cited by 0SourcecodeScholar
2026

cMoLLM at Scale: Horizontal Scaling Laws for Convolutionally-Gated Mixture-of-LLMs

ICML 2026poster

Scaling large language models (LLMs) has driven their success, yet dense Transformers couple capacity and computation: every parameter is activated for every token, making training and inference costs grow linearly with model size—a critical bottleneck as models approach trillion-parameter regimes. …

Cited by 0SourceScholar
2025

Fabric Dynamic Motion Modeling and Collision Avoidance With Oriented Bounding Box

RA-L 2025

Avoiding collision between the fabric and the obstacle is critical to transport fabric piece in the garment factory. If the fabric collides with the sharp-edged obstacle, it can be scratched or contaminated, resulting in poor product quality and increased waste. However, when we consider the fabric

Cited by 2SourceScholar