Papers by De Ma
VLASCD: A Visual Language Action Model for Simultaneous Chatting and Decision Making (2025.emnlp-main)
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| Challenge: | Recent large-scale pretrained models are built upon a multi-input single-output paradigm . tasks compete for a shared output channel, creating mutual exclusion effects . |
| Approach: | They propose a multi-input single-output (MISO) paradigm for large pretrained models . they propose unified training framework that enables concurrent multi-task outputs . |
| Outcome: | Experiments on autonomous driving platform show that MIMO-VLA outperforms state-of-the-art models in MIMO settings. |
SPEAK: Spiking Neurons as an Entropy-Aware Tokenizer for Large Language Models (2026.acl-long)
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| Challenge: | Existing tokenizers fail to explicitly leverage historical tokenization results . large language models (LLMs) have demonstrated remarkable effectiveness across NLP tasks . |
| Approach: | They propose a tokenizer that integrates spiking neurons to explicitly leverage historical tokenization results. |
| Outcome: | The proposed tokenizer leverages historical tokenization results, but does not selectively leverage history based on contextual relevance. |