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Xinyan Chen

9 accepted papers

2026

RF-MatID: Dataset and Benchmark for Radio Frequency Material Identification

ICLR 2026poster

Accurate material identification plays a crucial role in embodied AI systems, enabling a wide range of applications. However, current vision-based solutions are limited by the inherent constraints of optical sensors, while radio-frequency (RF) approaches, which can reveal intrinsic material properti…

Cited by 0SourcecodeScholar
2026

Thinking-while-Generating: Interleaving Textual Reasoning throughout Visual Generation

CVPR 2026

Recent advances in visual generation have increasingly explored the integration of reasoning capabilities. They incorporate textual reasoning, i.e., think, either before (as pre-planning) or after (as post-refinement) the generation process, yet they lack on-the-fly multimodal interaction during the

Cited by 0SourcecodeScholar
2026

Zero-Shot Open-Vocabulary Human Motion Grounding with Test-Time Training

AAAI 2026technical

Understanding complex human activities demands the ability to decompose motion into fine-grained, semantic-aligned sub-actions. This motion grounding process is crucial for behavior analysis, embodied AI and virtual reality. Yet, most existing methods rely on dense supervision with predefined action

Cited by 0SourcePDFScholar
2025

MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning

NeurIPS 2025poster

Chain-of-Thought (CoT) has widely enhanced mathematical reasoning in Large Language Models (LLMs), but it still remains challenging for extending it to multimodal domains. Existing works either adopt a similar textual reasoning for image input, or seek to interleave visual signals into mathematical…

Cited by 0SourcecodeScholar
2025

MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency

ICML 2025poster

Answering questions with Chain-of-Thought (CoT) has significantly enhanced the reasoning capabilities of Large Language Models (LLMs), yet its impact on Large Multimodal Models (LMMs) still lacks a systematic assessment and in-depth investigation. In this paper, we introduce **MME-CoT**, a specializ…

Cited by 0SourcePDFScholar
2024

Learning from Mistakes: Iterative Prompt Relabeling for Text-to-Image Diffusion Model Training

EMNLP 2024finding

Diffusion models have shown impressive performance in many domains. However, the model’s capability to follow natural language instructions (e.g., spatial relationships between objects, generating complex scenes) is still unsatisfactory. In this work, we propose Iterative Prompt Relabeling (IPR), a…

2023

MM-Fi: Multi-Modal Non-Intrusive 4D Human Dataset for Versatile Wireless Sensing

NeurIPS 2023poster

4D human perception plays an essential role in a myriad of applications, such as home automation and metaverse avatar simulation. However, existing solutions which mainly rely on cameras and wearable devices are either privacy intrusive or inconvenient to use. To address these issues, wireless sensi…