Internal Generation Record
Internal generation metadata: 453 candidate papers.
Generation Record
This page preserves selected papers, candidate scale, and source-date metadata for traceability. The page only changes presentation, not selected papers, ordering, or counts.
Internal generation record. Fetched at 2026-07-01T22:38:26.173615+00:00. Generated at 2026-07-01T22:39:42.587577+00:00. Machine-readable details stay under data/processed and data/reports.
Selected papers
| Rank | Takeaway | Topic | arXiv |
|---|---|---|---|
| 1 | strengthen multimodal understanding of charts, documents, and visual evidence | Training and Post-training | 2606.31732 |
| 2 | improve model reasoning, planning, and verification | Training and Post-training | 2606.31645 |
| 3 | make agents use tools and reusable skills more reliably | Benchmarks and Evaluation | 2606.31179 |
| 4 | make RAG retrieval and knowledge-base QA more reliable | Benchmarks and Evaluation | 2606.31127 |
| 5 | strengthen multimodal understanding of charts, documents, and visual evidence | Vision and Image Generation | 2606.32012 |
| 6 | improve code generation, execution feedback, and automated repair | Code Intelligence | 2606.31993 |
| 7 | make agents use tools and reusable skills more reliably | Benchmarks and Evaluation | 2606.31966 |
| 8 | improve model reasoning, planning, and verification | Benchmarks and Evaluation | 2606.31800 |
| 9 | make RAG retrieval and knowledge-base QA more reliable | Interpretability | 2606.31742 |
| 10 | improve image generation, visual understanding, and controllable rendering | Benchmarks and Evaluation | 2606.31700 |
| 11 | improve code generation, execution feedback, and automated repair | Vision and Image Generation | 2606.31603 |
| 12 | make agents use tools and reusable skills more reliably | Benchmarks and Evaluation | 2606.31461 |
| 13 | improve code generation, execution feedback, and automated repair | Video Generation | 2606.31198 |
| 14 | improve code generation, execution feedback, and automated repair | Code Intelligence | 2606.31082 |
| 15 | strengthen multimodal understanding of charts, documents, and visual evidence | Multimodal Models | 2606.31054 |
| 16 | make agents use tools and reusable skills more reliably | Agents and Tool Use | 2606.31023 |
| 17 | make RAG retrieval and knowledge-base QA more reliable | Vision and Image Generation | 2606.32039 |
| 18 | strengthen multimodal understanding of charts, documents, and visual evidence | Safety and Alignment | 2606.31876 |
| 19 | make agents use tools and reusable skills more reliably | Code Intelligence | 2606.31467 |
| 20 | make RAG retrieval and knowledge-base QA more reliable | Retrieval and RAG | 2606.31184 |
| 21 | improve model reasoning, planning, and verification | Benchmarks and Evaluation | 2606.31169 |
| 22 | improve code generation, execution feedback, and automated repair | Code Intelligence | 2606.31159 |
| 23 | make agents use tools and reusable skills more reliably | Benchmarks and Evaluation | 2606.31154 |
| 24 | make agents use tools and reusable skills more reliably | Robotics and Embodied AI | 2606.31144 |
| 25 | improve code generation, execution feedback, and automated repair | Systems and Deployment | 2606.32020 |
| 26 | strengthen multimodal understanding of charts, documents, and visual evidence | Multimodal Models | 2606.32016 |