ICLR 2026 - Submissions
Submissions
Summary Statistics
| Quantity AI Content | Count | Avg Rating |
|---|---|---|
| 0-10% | 1 (100%) | 2.00 |
| 10-30% | 0 (0%) | N/A |
| 30-50% | 0 (0%) | N/A |
| 50-70% | 0 (0%) | N/A |
| 70-90% | 0 (0%) | N/A |
| 90-100% | 0 (0%) | N/A |
| Total | 1 (100%) | 2.00 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| AdaptiveResidual: Inference-Time Trust Calibration for Contextual Knowledge Injection | In modern large language models (LLMs), injecting external knowledge via the context to guide models' outputs toward desired outcomes (e.g., through RAG) is a standard practice. However, recent resea... | 2.00 | 2% | See Reviews | View AI Dashboard |