Papers with TARS
Medical Coding with Biomedical Transformer Ensembles and Zero/Few-shot Learning (2022.naacl-industry)
Copied to clipboard
| Challenge: | Medical coding (MC) is an essential pre-requisite for reliable data retrieval and reporting. |
| Approach: | They propose a method to classify medical terms into standardized alphanumerical terms and codes . they use a combination of traditional BERT-based classification and a zero/few-shot learning approach . |
| Outcome: | The proposed approach outperforms baselines in the few-shot regime. |
Closing the Modality Reasoning Gap for Speech Large Language Models (2026.acl-long)
Copied to clipboard
| Challenge: | Recent advances in Speech Large Language Models have a modality reasoning gap that is not addressed by prior work. |
| Approach: | They propose a reinforcement-learning framework that aligns text-conditioned and speech-conditioned trajectories through an asymmetric reward design. |
| Outcome: | Experiments on MMSU and OBQA show that the proposed framework narrows the modality reasoning gap and achieves state-of-the-art performance among 7B-scale Speech LLMs. |