{
  "timestamp": "2026-09-13T09:00:00Z",
  "task": "t_0f1adf2f",
  "operator": "r-and-d",
  "arxiv_papers": [
    {
      "id": "2609.00935",
      "title": "DualStake: Dual-Path Confidence Calibration in Deep Research Agents",
      "authors": ["Yinuo Xu", "Yuwei Liang", "Jianjie Cheng", "Meng Wang", "Yongcan Yu", "Shuo Lu", "Jian Liang"],
      "date": "2026-09-01",
      "url": "https://arxiv.org/abs/2609.00935",
      "github": "https://github.com/FloXXXt/DualStake",
      "summary": "Augments the Deep Research pipeline with step confidence elicitation after each retrieval (Evidence Confidence) and Answer Confidence. Introduces DualStake, a dual-path calibration method applying margin-clipped, confidence-dependent stake rewards to align both confidences with answer correctness."
    },
    {
      "id": "2609.01294",
      "title": "Explore Before Committing: Hypothesis-Guided Search for Deep Research Agents",
      "authors": ["Ruochen Zhou", "Zhengyu Chen", "Luan Zhang", "Siyang Gao", "Yee Whye Teh", "Shiqi Chen"],
      "date": "2026-09-01",
      "url": "https://arxiv.org/abs/2609.01294",
      "summary": "Identifies single trajectory commitment as a major failure mode. Proposes HypoSearch which generates lightweight hypotheses as soft search hints, explores bounded independent branches, and compares branch-level evidence before commitment."
    },
    {
      "id": "2608.29606",
      "title": "Agent Zero Memory: Provenance-Aware Long-Term Memory for LLM Agents",
      "authors": ["Ming Wu", "Pengyuan Zhu"],
      "date": "2026-08-30",
      "url": "https://arxiv.org/abs/2608.29606",
      "summary": "Presents a provenance-aware long-term memory system that distils interactions into an episodic Memory Events timeline, an associative entity-event knowledge graph, and a semantic citation-locked HDM. Sets SOTA on LongMemEval and LoCoMo."
    },
    {
      "id": "2606.00610",
      "title": "MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation",
      "authors": ["Chuanjie Wu", "Zhishang Xiang", "Yunbo Tang", "Zerui Chen", "Qinggang Zhang", "Jinsong Su"],
      "date": "2026-05-30",
      "url": "https://arxiv.org/abs/2606.00610",
      "github": "https://github.com/XMUDeepLIT/MemGraphRAG",
      "summary": "Introduces a collaborative society of agents supported by shared memory to ensure high-quality graph construction for GraphRAG, dynamically resolving logical conflicts across fragmented corpora."
    },
    {
      "id": "2605.22142",
      "title": "Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability",
      "authors": ["Taewoon Kim", "Vincent François-Lavet", "Michael Cochez"],
      "date": "2026-05-21",
      "url": "https://arxiv.org/abs/2605.22142",
      "summary": "Casts short-term to long-term memory transfer in a temporal knowledge-graph as a neuro-symbolic value-based decision problem using per-item Q-learning to choose which triples to retain."
    }
  ],
  "graft_analysis": {
    "repo": "https://github.com/FloXXXt/DualStake",
    "files_analyzed": 183,
    "symbols": 1492,
    "edges": 3877,
    "key_findings": [
      "GenerationConfig and LLMGenerationManager control the generation process with rolling state and GPU padding.",
      "DualStake logic is located in verl/trainer/conf_adv_config.py where apply_dual_calib_to_scores processes lsc_confs (last step confidence) and fc_confs (final confidence).",
      "Retrieval logic in search_r1 handles both BM25 and Dense Retrieval models."
    ]
  }
}