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Freshness: newest result fetched 24 d ago · median age of these results 24 d · 1 of 30 carry a fetch time
https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv
https://arxiv.org/abs/2608.03883
The task requires systems to rank candidate Reddit sentences according to their relevance to each of the 18 symptoms in the Adult ADHD Self-Report Scale (ASRS-v1
https://arxiv.org/abs/2104.08663
Benchmark for Zero-shot Evaluation of Information Retrieval Models, by Nandan Thakur and 4 other authors
View PDF HTML (experimental)
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/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/html/2407.00575v3
In large-scale systems, obtaining performance guarantees is challenging even with cooperative players since they do not know the reward functions of their peers
https://arxiv.org/html/2608.03452v1
And among five architectures varying in positional encoding and tag representation, position-invariant tag encoding enables acquisition of the L-shaped paradigm even when L-shaped verbs are scarce, though no architecture generalizes like humans (Kakolu Ramarao et al
https://arxiv.org/html/2607.28323v1
3 Target execution schedules
7 Concluding Remarks
8 Proof of Theorem 3
https://arxiv.org/html/2607.27063v1
3 Empirical measurement of herding
3 Agent-based market model
3
https://arxiv.org/html/2609.03027v1
Despite this enormous improvement over a conventional correlator-based architecture, it is estimated that the scalability of EPIC on GPUs is limited even on advanced systems like the H100 because of the shared memory constraints [26]
https://arxiv.org/html/2608.02966v1
Difficulty-Gated Guessing Fallback
An Approximation of Difficulty Index
https://arxiv.org/html/2608.03099v1
Even when actions are directly conditioned on language, system-level success does not by itself isolate language’s contribution
https://arxiv.org/html/2607.29281v2
Ideally, researchers would like to commit to a choice of the three elements listed above such that they are certain that, even in the worst case admitted by those minimal assumptions, such choices will not be too far from being optimal
https://arxiv.org/html/2608.03233v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.02668v1
Both prove to be members of a one-parameter family of angular retractions, pp-SpheretNorm, whose rotation angle saturates rather than growing without bound
https://arxiv.org/pdf/2608.03157
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https://arxiv.org/html/2608.03529v1
To our knowledge, different measures, such as embeddings, Natural Language Inference (NLI)-models or LLMs for measuring semantic equivalence in soft IRR have not been systematically compared in terms of performance and failure modes
https://arxiv.org/html/2609.02852v1
A linguistically-decodable feature is one that is defined in terms of natural language, and is extracted directly from a model’s natural-language outputs or indirectly via mechanistic probes like sparse autoencoders Bricken et al
https://arxiv.org/html/2608.02813v1
SY] 03 Aug 2026
Coordinated Primary Frequency Regulation and Grid-Forming Control for Wind Turbine Generators
Meng Chen, Yufei Xi, Lin Cheng, Florian Döfler, and Ioannis Lestas Meng Chen and Ioannis Lestas are with the Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, United Kingdom
https://arxiv.org/html/2608.03358v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.00648v1
MA] 01 Aug 2026
MDGAM-Based Cooperative Task Scheduling for Communication-Constrained Distributed Multi-Agent Systems
Licheng Wang Mingtao Huang Yuan Shen Thanks: The authors are with the Department of Electronic Engineering, and Beijing National Research Center for Information Science and Technology
https://arxiv.org/html/2608.03655v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.03545v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.00328v2
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.03063v1
Offline comparison of deployment candidates (RQ3, Table 13)
https://arxiv.org/html/2608.03141v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.01085v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/pdf/2205.01882v5
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https://arxiv.org/pdf/2608.02817
1) /Title (Reviving Micro Real Rigidities: The Importance of Demand Shocks) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2607.26188v1
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