GATHER finds topological convergence nodes in a cell-centric knowledge graph to compress multi-gene signals into compact evidence for zero-shot cell-type annotation with a single LLM call.
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6 Pith papers cite this work, alongside 44 external citations. Polarity classification is still indexing.
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years
2026 6verdicts
UNVERDICTED 6representative citing papers
AdaSID adaptively regulates semantic ID overlaps in multimodal recommendations to improve retrieval performance, codebook utilization, and downstream metrics like GMV.
NeocorRAG uses Evidence Chains to achieve SOTA retrieval quality in RAG on HotpotQA, 2WikiMultiHopQA, MuSiQue, and NQ for 3B and 70B models while using under 20% of the tokens of comparable methods.
Rabtriever distills a generative reranker into an efficient bi-encoder using on-policy JEPA to achieve near-reranker accuracy with linear complexity on rationale-based retrieval.
SkipDisk is a disk-memory hybrid ANN search that achieves 63-85% of HNSW latency at 10-20% memory footprint via dedicated pivots for tighter lower bounds, three-level pruning, and decoupled async I/O.
The paper reviews conceptual foundations, methodological innovations, effective designs, critical challenges, and future directions for LLM-based Agentic Reinforcement Learning.
citing papers explorer
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GATHER: Convergence-Centric Hyper-Entity Retrieval for Zero-Shot Cell-Type Annotation
GATHER finds topological convergence nodes in a cell-centric knowledge graph to compress multi-gene signals into compact evidence for zero-shot cell-type annotation with a single LLM call.
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Beyond Static Collision Handling: Adaptive Semantic ID Learning for Multimodal Recommendation at Industrial Scale
AdaSID adaptively regulates semantic ID overlaps in multimodal recommendations to improve retrieval performance, codebook utilization, and downstream metrics like GMV.
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NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains
NeocorRAG uses Evidence Chains to achieve SOTA retrieval quality in RAG on HotpotQA, 2WikiMultiHopQA, MuSiQue, and NQ for 3B and 70B models while using under 20% of the tokens of comparable methods.
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Efficient Rationale-based Retrieval: On-policy Distillation from Generative Rerankers based on JEPA
Rabtriever distills a generative reranker into an efficient bi-encoder using on-policy JEPA to achieve near-reranker accuracy with linear complexity on rationale-based retrieval.
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Low-Latency Out-of-Core ANN Search in High-Dimensional Space
SkipDisk is a disk-memory hybrid ANN search that achieves 63-85% of HNSW latency at 10-20% memory footprint via dedicated pivots for tighter lower bounds, three-level pruning, and decoupled async I/O.
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Rethinking Agentic Reinforcement Learning In Large Language Models
The paper reviews conceptual foundations, methodological innovations, effective designs, critical challenges, and future directions for LLM-based Agentic Reinforcement Learning.