ICLR 2025 Past Other
I Can't Believe It's Not Better: Challenges in Applied Deep Learning
ICLR 2025 Workshop ICBINB
- Submission deadline
- Feb 7, 2025, 11:59 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (28)
Fetched from OpenReview (v2) on 2026-06-10.
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An Integrated YOLO and VLM System for Fire Detection in Enclosed Environments
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Are We Really Unlearning? The Presence of Residual Knowledge in Machine Unlearning
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Bridging the Language Gap: Evaluating Machine Translation for Animal Health in Low-Resource Settings
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Challenges of Decomposing Tools in Surgical Scenes Through Disentangling The Latent Representations
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Challenges of Multi-Modal Coreset Selection for Depth Prediction
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Data Mixing can Induce Phase Transitions in Knowledge Acquisition
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Do Not Overestimate Black-box Attacks
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Fantastic Allosteric Binding Sites and Why Deep Learning Cannot Find Them
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From Fog to Failure: The Unintended Consequences of Dehazing on Object Detection in Clear Images
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Graph Networks Struggle With Variable Scale
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How Effective Are AI Models in Translating English Scientific Texts to Nigerian Pidgin: A Low-resource Language?
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Impact of Task Phrasing on Presumptions in Large Language Models
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In Search of Forgotten Domain Generalization
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Know Thy Judge: On the Robustness Meta-Evaluation of LLM Safety Judges
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Last Layer Empirical Bayes
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Lost-in-distance: Impact of Contextual Proximity on LLM Performance in Graph Tasks
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Modeling speech emotion with label variance and analyzing performance across speakers and unseen acoustic conditions
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Not constructing Ramsey Graphs using Deep Reinforcement Learning
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On the Limitations of LLM-Synthesized Social Media Misinformation Moderation
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On the Limitations of Neural Networks for Option Pricing: Analysis of Volatility Regime Sensitivity
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On the Limits of Applying Graph Transformers for Brain Connectome Classification
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On the Power of Heuristics in Temporal Graphs
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On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis
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On the Role of Structure in Hierarchical Graph Neural Networks
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Overtrained Language Models Are Harder to Fine-Tune
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Performance of Zero-Shot Time Series Foundation Models on Cloud Data
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Possibility for Proactive Anomaly Detection
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Rethinking Evaluation for Temporal Link Prediction through Counterfactual Analysis