Papers by Guangrun Wang
Stable Language Guidance for Vision–Language–Action Models (2026.acl-long)
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| Challenge: | Existing vision-Language-Action models are notoriously brittle to linguistic perturbations. |
| Approach: | They propose a probabilistic framework that disentangles physical affordance from semantic execution. |
| Outcome: | The proposed framework disentangles physical affordance from semantic execution. |
EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation (2021.findings-emnlp)
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| Challenge: | Pre-trained language models have shown remarkable results on various NLP tasks. |
| Approach: | They propose to improve the feed-forward network (FFN) in BERT with a higher computational cost than improving the multi-head attention (MHA). |
| Outcome: | The proposed model is 6.9 smaller and 4.4 faster than BERTBASE and has competitive performances on GLUE and SQuAD Benchmarks. |