Papers with robust discrimination

2 papers
From Imitation to Discrimination: Progressive Curriculum Learning for Robust Web Navigation (2026.findings-acl)

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Challenge: Text-based web agents offer computational efficiency for autonomous web navigation, yet they lack discrimination capabilities to reject plausible but incorrect elements in densely populated pages.
Approach: They propose a model that uses a text-based web agent to learn to discriminate against incorrect elements in densely populated HTML and a training curriculum to synthesize diverse cross-domain tasks with strict verification.
Outcome: Empirical evaluation shows that the model performs better than open-source models with 58.7% step success rate.
HCFD: A Benchmark for Audio Deepfake Detection in Healthcare (2026.findings-acl)

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Challenge: a new task for detecting codec-fakes under pathological speech conditions is presented . we focus on codec based synthetic speech since neural codec decoding is a core building block in speech generation pipelines.
Approach: They propose a new task for detecting codec-fakes under pathological speech conditions . they focus on codec based synthetic speech since neural codec decoding is a core building block in speech pipelines .
Outcome: The proposed framework outperforms speech-based models on Healthcare CodecFake . it achieves the strongest performance on the task across clinical conditions and codecs .

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