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Consequently, additional context is required to provide out-of-domain (OOD) knowledge and reduce hallucinations
from the top result below
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/2608.03048v1
com/JetAstra/PI-Mem
Introduction
The ability to reason over long contexts is increasingly important for large language models (LLMs), supporting applications such as long-document question answering (Gemini Team 2025; Yang et al
https://arxiv.org/html/2608.02613v1
Then it must make an even harder judgment: even if the answer is known, is it actually appropriate to tell Bob
https://arxiv.org/list/cs.CL/new
Accepted to C3NLP @ ACL 2026
Subjects: Computation and Language (cs
https://arxiv.org/list/cs.AI/new
Our approach utilizes a two-stage generation process: first, the model is prompted to self-select a unique, idiosyncratic persona to anchor its starting point; second, we apply a dual-stage sampling sieve, utilizing Top-$p$ filtering to preserve grammatical validity followed by extreme temperature scaling ($T \ge 4
https://arxiv.org/list/cs.IR/new
IR)
Industrial recommenders increasingly adopt the pretrain-then-transfer paradigm, yet behavioral distribution drift raises two questions: what to learn from behavior sequences, and how to transfer the learned knowledge while the pretrained model is continually refreshed
https://arxiv.org/list/cs.IR/recent
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Information Retrieval
Authors and titles for recent submissions
Wed, 5 Aug 2026
https://arxiv.org/abs/2608.03883
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https://arxiv.org/abs/2104.08663
Our results show BM25 is a robust baseline and re-ranking and late-interaction-based models on average achieve the best zero-shot performances, however, at high computational costs
https://arxiv.org/html/2407.16741v3
edu
Abstract
Software is one of the most powerful tools that we humans have at our disposal; it allows a skilled programmer to interact with the world in complex and profound ways
https://arxiv.org/abs/2608.03860
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https://arxiv.org/abs/1411.2842
2842] Logical Limitations to Machine Ethics with Consequences to Lethal Autonomous Weapons
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arXiv is now an independent nonprofit
https://arxiv.org/list/cs.SI/new
These results are early evidence that access to many independent feeds is not enough to give identical texts equal exposure
https://arxiv.org/list/econ.GN/recent
00328 [pdf, html, other]
Title: Global coal trade is resilient to maritime chokepoints
Jorrit Gosens, Alex B
https://arxiv.org/pdf/2607.26327v3
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https://arxiv.org/list/cs.LG/2024-12
3251-3298
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[1] arXiv:2412
https://arxiv.org/list/cs.CY/current
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[1] arXiv:2608
https://arxiv.org/abs/2607.29380
Early labor market and clinical evidence suggests possible disruption to expertise-regeneration pathways in highly AI-exposed sectors, though adoption is recent and the strongest signals come from leading sectors rather than all professions
https://arxiv.org/abs/2510.01395
01395] Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence
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arXiv is now an independent nonprofit
https://arxiv.org/src/2006.02318
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https://arxiv.org/src/2006.03178
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https://arxiv.org/pdf/2608.02833
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https://arxiv.org/pdf/2609.03103
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https://arxiv.org/src/2002.02145
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https://arxiv.org/pdf/2407.00345
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https://arxiv.org/pdf/2407.02402
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https://arxiv.org/pdf/2608.02609
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https://arxiv.org/html/2508.08980v3
When decision-makers face complex or unfamiliar alternatives, however, it is often unreasonable to require their preferences to be complete or even transitive
https://arxiv.org/pdf/2508.02686
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https://arxiv.org/pdf/2608.02943
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