Papers with FDA
RegNLI: Detecting Online Product Misbranding through Legal and Linguistic Alignment (2026.eacl-industry)
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| Challenge: | Existing approaches to claim verification focus on keyword matching or generic text classification . misbranding involves deceptive labeling or advertising that misleads consumers about a product's nature or quality . |
| Approach: | They propose a framework that formulates misbranding detection as an inference task between product claims and regulatory provisions. |
| Outcome: | The proposed framework outperforms baselines in misbranding detection and regulation alignment metrics. |
Towards More Efficient Post-training via Fourier Domain Adapter Framework (2025.findings-emnlp)
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| Challenge: | FDA reparameterizes the core projection operation of the adapter module directly in the Fourier domain. |
| Approach: | They propose a framework that reparameterizes the core projection operation of the adapter module directly in the Fourier domain. |
| Outcome: | The proposed framework outperforms existing parameter-efficient fine-tuning methods on GLUE, E2E NLG, and instruction tuning benchmarks. |
Reason to Rote: Rethinking Memorization in Reasoning (2025.emnlp-main)
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| Challenge: | Large language models readily memorize arbitrary training instances, such as label noise . however, such memorization does not affect generalizable reasoning abilities . |
| Approach: | They investigate how large language models memorize label noise and why it affects generalizability. |
| Outcome: | The proposed model performs well on reasoning tasks even when memorized labels are missing . the proposed model is able to generalize to correctly answer "87+19=106" |
Scaling up the State Size of RNN LLMs for Long-Context Scenarios (2025.acl-long)
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| Challenge: | Existing RNN-based LLMs struggle with long-context scenarios due to their quadratic computational complexity and linear memory requirements. |
| Approach: | They propose an efficient scaling method to scale RNN models to match the 2k context length of Transformers with small parameters overhead. |
| Outcome: | The proposed method improves long-context understanding and improves performance on FDA recall-intensive tasks. |
From Regulatory Approvals to Patents: Cross-Domain Linking for Cardiovascular Device Traceability (2026.acl-long)
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| Challenge: | a new cross-domain entity linking problem exists between FDA-approved medical devices and patents . a recent study compared the semantics of FDA documents with patents, resulting in minimal overlap . |
| Approach: | They propose a framework that links FDA-approved medical devices to their patents . they propose 'MedDevKG' framework that integrates a domain-specific ontology . |
| Outcome: | The proposed framework outperforms existing methods in lower-bound recalls and noise reductions. |