2026-07-29

Internal Generation Record

Internal generation metadata: 335 candidate papers.

Published 2026-07-29 Target source 2026-07-27 Actual source 2026-07-27 Candidates 335 Featured 6 Tracked 20

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 2026-07-28T22:14:18.266515+00:00. Generated at 2026-07-28T22:15:34.394287+00:00. Machine-readable details stay under data/processed and data/reports.

Selected papers

RankTakeawayTopicarXiv
1improve code generation, execution feedback, and automated repairSystems and Deployment2607.24184
2make agents use tools and reusable skills more reliablyRobotics and Embodied AI2607.24672
3improve code generation, execution feedback, and automated repairBenchmarks and Evaluation2607.24519
4make RAG retrieval and knowledge-base QA more reliableTraining and Post-training2607.24683
5make agents use tools and reusable skills more reliablyRetrieval and RAG2607.24512
6improve code generation, execution feedback, and automated repairData Engineering2607.24365
7make agents use tools and reusable skills more reliablyAgents and Tool Use2607.24339
8improve model reasoning, planning, and verificationMultimodal Models2607.23944
9improve model reasoning, planning, and verificationSystems and Deployment2607.24555
10improve model reasoning, planning, and verificationReasoning and Planning2607.24471
11strengthen multimodal understanding of charts, documents, and visual evidenceMultimodal Models2607.24353
12make agents use tools and reusable skills more reliablyRetrieval and RAG2607.24313
13make RAG retrieval and knowledge-base QA more reliableSafety and Alignment2607.24243
14make agents use tools and reusable skills more reliablyTraining and Post-training2607.24057
15make RAG retrieval and knowledge-base QA more reliableRetrieval and RAG2607.24015
16test temporal consistency and motion realism in video generationBenchmarks and Evaluation2607.23987
17improve model reasoning, planning, and verificationRobotics and Embodied AI2607.23899
18make agents use tools and reusable skills more reliablyAgents and Tool Use2607.24744
19make agents use tools and reusable skills more reliablyMultimodal Models2607.24707
20make RAG retrieval and knowledge-base QA more reliableMultimodal Models2607.24701
21improve code generation, execution feedback, and automated repairBenchmarks and Evaluation2607.24688
22improve model reasoning, planning, and verificationBenchmarks and Evaluation2607.24611
23make agents use tools and reusable skills more reliablyCode Intelligence2607.24604
24make agents use tools and reusable skills more reliablyAgents and Tool Use2607.24588
25make agents use tools and reusable skills more reliablyBenchmarks and Evaluation2607.24577
26strengthen multimodal understanding of charts, documents, and visual evidenceBenchmarks and Evaluation2607.24560