Papers with CAM
CAM 2.0: End-to-End Open Domain Comparative Question Answering System (2024.lrec-main)
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Ahmad Shallouf, Hanna Herasimchyk, Mikhail Salnikov, Rudy Alexandro Garrido Veliz, Natia Mestvirishvili, Alexander Panchenko, Chris Biemann, Irina Nikishina
| Challenge: | Comparative Question Answering is a Natural Language Processing task that combines Question Answers and Argument Mining. |
| Approach: | They propose a system for answering comparative questions called CAM 2.0 and a public leaderboard called CompUGE that unifies existing datasets under a single easy-to-use evaluation suite. |
| Outcome: | The proposed system is compared with previous web-form-based systems . it features question identification, object and aspect labeling, stance classification, summarization . the proposed system has a user-friendly interface and is available for free on the web . |
Diffusion-CAM: Faithful Visual Explanations for dMLLMs (2026.acl-long)
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| Challenge: | Existing Class Activation Mapping methods are ill-suited for interpreting non-autoregressive behaviors of diffusion-based architectures. |
| Approach: | They propose to use a method to generate parallel activation maps by probing intermediate representations in the transformer backbone to capture latent features and their class-specific gradients. |
| Outcome: | Experiments show that Diffusion-CAM significantly outperforms SoTA methods in localization accuracy and visual fidelity. |