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MMD) to implicitly enhance cross-modal distribution consistency
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https://arxiv.org/list/cs.CL/new
On the held-out Akkademia validation split (2,812 samples), we report 49
https://arxiv.org/list/cs.AI/new
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https://arxiv.org/html/2501.13956v1
Consequently, additional context is required to provide out-of-domain (OOD) knowledge and reduce hallucinations
https://arxiv.org/html/2608.02613v1
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/html/2608.03048v1
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https://arxiv.org/html/2607.22511v2
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https://arxiv.org/abs/2104.08663
Benchmark for Zero-shot Evaluation of Information Retrieval Models, by Nandan Thakur and 4 other authors
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Abstract:Existing neural information retrieval (IR) models have often been studied in homogeneous and narrow settings, which has considerably limited insights into their out-of
https://arxiv.org/html/2608.02609v1
On the held-out Akkademia validation split (2,812 samples), we report 49
https://arxiv.org/abs/2608.03883
Our systems combine sparse BM25 retrieval, evidence-aware rescoring for self-referential symptom reports, embedding-based reranking, query-prototype expansion, and LLM-based reranking
https://arxiv.org/abs/2608.03860
The pipeline combines sentence-window chunking, BM25, BGE-M3 dense retrieval, reciprocal rank fusion, optional cross-encoder reranking, and grounded answer generation
https://arxiv.org/list/cs.IR/recent
IR)
Tue, 4 Aug 2026 (showing first 34 of 45 entries )
[17] arXiv:2608
https://arxiv.org/html/2608.03138v1
Experiments show that StructPO improves semantic alignment, structural rationality and inference efficiency over workflow-based baselines, generalizes to out-of-domain settings, and remains competitive with GPT-5
https://arxiv.org/html/2608.03154v1
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arXiv:2608
https://arxiv.org/html/2607.26327v3
I thank an anonymous reader of an earlier draft for comments that prompted the institutional extension in Section 4, and further rounds of critical comments for prompting the power analysis of Appendix C, the coverage-boundary discussion in Section 4
https://arxiv.org/html/2608.01366v2
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.03703v1
index complexes and leveraged volatility products — impact per unit of flow is modest, declines in predictability, and is partly offset by contrarian flows into and out of the funds (Ivanov and Lenkey 2018; Brøgger 2021; Barbon et al
https://arxiv.org/list/cs.IR/new
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https://arxiv.org/html/2608.02625v1
Draft–then–refine and progressive diffusion
https://arxiv.org/html/2407.16741v3
2 OpenHands Architecture
2.1 Agent Definition and Implementation
2.2 Agent Runtime: How Execution of Actions Results in Observations
2.3 Agent Skills: The Extensible Agent-Computer Interface
2.4 Agent Delegation: Cooperative Multi-agent
https://arxiv.org/html/2608.02817v1
The authors are grateful for the invaluable feedback they received on an earlier draft from Jón Steinsson
https://arxiv.org/list/math/new
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[1] arXiv:2608