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The query asks the model to recall the topic of an earlier conversation about Tesla; the gold answer is anchored in one specific session about Pooja’s dig site
from the top result below

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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

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
We demonstrate that it can self-assemble functional circuits from scratch and rapidly re-route logic around permanent, previously unseen hardware faults

Rainfall is rough

https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license arXiv:2607

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
We use brain MRI as a controlled, high-stakes testbed for a broader failure mode in frontier multimodal systems: models can appear competent while lacking reliable self-knowledge

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https://arxiv.org/html/2608.03048v1
for large language models, as recent recurrent-memory approaches face two inherent challenges: sequential chunk-wise updates can overwrite early critical evidence with later irrelevant content, and serial inter-chunk dependencies limit parallelism and cause latency to increase with context length

1 Introduction

https://arxiv.org/html/2501.13956v1
com Abstract We introduce Zep, a novel memory layer service for AI agents that outperforms the current state-of-the-art system, MemGPT, in the Deep Memory Retrieval (DMR) benchmark

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https://arxiv.org/html/2609.02852v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

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https://arxiv.org/html/2609.03027v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

Stabilization of First-Order Partial Integro-Differential Equations with

https://arxiv.org/html/2608.02851v1
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/html/2607.22511v2
A statement can be free of sorry and still be mathematically uninformative: a definition may reduce to True; or an unproven step may be introduced as an axiom that the kernel accepts

1 Introduction

https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands Slack http://bit

Computation and Language

https://arxiv.org/list/cs.CL/new
LG) Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, leaving a 4,000-year cultural barrier that existing NLP tools have only partially addressed

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https://arxiv.org/html/2608.02612v1
org perpetual non-exclusive license arXiv:2608

Cryptography and Security

https://arxiv.org/list/cs.CR/new
We also show that coarse-to-fine label selection can create near-perfect measured correlation without learned dependence

Underspecification in Language Modeling Tasks: A Causality-Informed

https://arxiv.org/html/2210.00131v4
Code and open-source demos available at https://github

Software Engineering

https://arxiv.org/list/cs.SE/new
Through an analysis of 1,966 open source projects, 1,355 Github issues, 444 CVE reports, and 361 StackOverflow posts, we systematically map the feature support and real-world usage of globs across six common ecosystems that utilize globs

1 Introduction

https://arxiv.org/html/2511.06451v1
Spectral safety and discrete Green kernel

Mathematics

https://arxiv.org/list/math/new
Their finite iterates can develop rapidly increasing numbers of linear pieces, making them a natural test case for the expressive power of deep neural networks

[2608.03883] DS@GT-ARC at eRisk 2026 Task 3: Sparse, Semantic, and LLM

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

[2608.03860] SciRet: A Compute-Aware Empirical Study of Retrieval and

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

[2104.08663] BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of

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

Information Retrieval

https://arxiv.org/list/cs.IR/recent
02048 [pdf, html, other] Title: SmartGR: Hierarchy and Beam-Aware Knowledge Distillation for Generative Recommendation Ziheng Zhang, Yu Cui, Bohao Wang, Yong He, Chao Yu, Chuan Yuan, Wujie Sun, Can Wa

Machine Learning Dec 2022

https://arxiv.org/list/cs.LG/2022-12
Skip to main content System maintenance August 4th and 5th Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Machine Learning Authors and titles for December 2022 Total of 2004 entries : 1

Statistics Theory Mar 2024

https://arxiv.org/list/math.ST/2024-03
00186 [pdf, html, other] Title: Warped Kernel Estimator for I

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https://arxiv.org/html/2609.03371v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

Information Retrieval

https://arxiv.org/list/cs.IR/new
Our results show that skill representation itself matters, and that simply preserving the structure already present in skill files can substantially improve retrieval

Microstructural Foundations of Rough Noise1footnote

https://arxiv.org/html/2607.29442v2
In an asymptotic framework inspired by Rosenbaum2018, we show that the rescaled price process converges to a Bachelier-type semimartingale plus a Gaussian moving average whose kernel is determined explicitly by the trawl function

Instrumentation and Methods for Astrophysics

https://arxiv.org/list/astro-ph.IM/new
In particular, the maximal light deflection of a given Solar System body can be easily estimated for a given observer

Machine Learning Dec 2024

https://arxiv.org/list/cs.LG/2024-12
Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Machine Learning Authors and titles for December 2024 Total of 3298 entries : 1-50 51-100 101-150 151-200 ... 3251-3298 Showing up

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https://arxiv.org/html/2608.03411v1
com Abstract Accurate Uncertainty Quantification (UQ) is critical for reliable deployment of Large Language Models (LLMs), yet traditional probability-based metrics often fail to capture the model’s true epistemic state