arXiv AI
Jul 17
Building Agent Harnesses for Scientific Curation from Multimodal Sources
arXiv:2606. 21005v2 Announce Type: replace Abstract: Scientific discovery workflows often depend on structured curation from the literature.
ScholarStack: Layered Research Asset Orchestration and Cross-Task Reuse for Scientific Agents
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arXiv AI
3d ago
Large Knowledge Model: A Knowledge Foundation for Agentic Science at Scale
arXiv:2609.27297v2 Announce Type: replace Abstract: Agentic science envisions many autonomous agents investigating concurrently while building on a shared, evolving body of scientific knowledge. This...
Hugging Face Trending Papers
Sep 23
Large Knowledge Model: From Papers to a Scientific Reasoning Landscape
Accumulated scientific knowledge advances inquiry when prior findings help researchers choose new questions, design investigations, and interpret results. Realizing this value at scale requires access...
arXiv AI
Jul 24
SciExplore: Evaluating Autonomous Agents from Scientific Navigation to Information Integration
arXiv:2607. 20926v1 Announce Type: new Abstract: Scientific research involves complex information-seeking and reasoning workflows across heterogeneous sources.
arXiv AI
Sep 24
Large Knowledge Model: From Papers to a Scientific Reasoning Landscape
The paper introduces the Large Knowledge Model (LKM), a scientific knowledge infrastructure that converts research literature into shared, computationally accessible reasoning graphs. LKM aligns questions, claims, and reasoning chains across papers, creating a Scientific Reasoning Landscape with Question, Workflow, and Evidence views. The system enhances scientific search, evidence‑grounded QA, and research planning, achieving notable accuracy gains on ChemBench, PubMedQA, and SciBench.
arXiv Machine Learning
Jul 31
AskChem: Claim-Centered Infrastructure for Chemistry Literature Synthesis
arXiv:2607. 28618v1 Announce Type: cross Abstract: Chemistry literature synthesis often requires assembling specific findings scattered across many publications, yet existing literature-search systems primarily return ranked document lists.
arXiv AI
3d ago
PathAnchor: Path-Structured Evidence for Scientific Agents
PathAnchor is a new scientific reasoning system that uses path-structured evidence workspaces instead of independent passages or concepts. It retrieves source-linked Material‑Sensor‑Signal‑System trajectories that preserve role, direction, and supporting evidence, and a controller uses read‑only tools to search, trace, and open exact evidence before producing a claim‑cited answer. In evaluations on 120 flexible‑sensor questions, PathAnchor achieved an 82.6% score, outperformed six other systems, and improved source recall, citation completeness, and reduced tool calls compared to unordered concept graphs.
arXiv AI
Jun 26
ProvenAI: Provenance-Native Traces of Evidence in Generated Answers
arXiv:2606. 26449v1 Announce Type: cross Abstract: Retrieval-augmented systems routinely present citations alongside generated answers, yet a citation does not confirm that the corresponding source meaningfully shaped the output.
arXiv AI
Jun 10
Agentic Hybrid RAG for Evidence-Grounded Muon Collider Analysis
arXiv:2606. 10381v1 Announce Type: cross Abstract: Muon collider research spans accelerator physics, detector instrumentation, and high-energy phenomenology, with relevant evidence scattered across a rapidly expanding and heterogeneous body of scientific literature.
arXiv Computation and Language
Sep 1
Extending AI for Research to the Humanities: A Multi-Agent Framework for Evidence-Grounded Scholarship
arXiv:2605.30947v4 Announce Type: replace Abstract: LLM-based research agents have advanced rapidly in science and engineering, where research is organized around executable experiments, code, and qu...
arXiv AI
4d ago
DeepSurvey: Agent-Oriented Automated Survey Generation with Analytical Depth and Citation Reliability
arXiv:2605.29522v2 Announce Type: replace Abstract: As scientific literature grows rapidly and research increasingly involves AI agents, automated survey generation has become a key capability for bo...
arXiv AI
Jul 13
WILDTRACE: Benchmarking Natural Evidence Trails in Long-Context Reasoning
arXiv:2607. 09328v1 Announce Type: cross Abstract: Answering complex questions over long documents frequently requires integrating evidence that the source itself disperses naturally across distant passages.