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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
A million-token cloud context window does not help here, as it requires off-device upload, which privacy-sensitive personal memory management is meant to avoid

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
Extending the pattern-generation paradigm of Neural Cellular Automata (NCA), it navigates the degenerate Boolean search space to satisfy a computational task, rather than regenerating a fixed target state

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https://arxiv.org/html/2510.03215v2
Report GitHub Issue Description: arXiv is now an independent nonprofit

Towards Real-world Environment-aware Zero-shot Text-to-speech Synthesis

https://arxiv.org/html/2608.03011v1
AS] 04 Aug 2026 Towards Real-world Environment-aware Zero-shot Text-to-speech Synthesis via Disentangled Audio Infilling Ye-Xin Lu, Xin Wang,  Yang Ai,  Hui-Peng Du,  Zhen-Hua Ling,  and Junichi Yamagishi This work is the extended version of our conference paper [1] published at IEEE International Conference on

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https://arxiv.org/html/2608.03048v1
6 million tokens and find that it outperforms the recurrent-memory baseline by +6

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

Sphere Retraction Normalizations

https://arxiv.org/html/2608.02668v1
com/hazdzz/deep_connection \ncudata[Correspondence]Jie Zhang (), Correspondence: Cheng-Fang Su () “Geometry is not true, it is advantageous

1 Introduction

https://arxiv.org/html/2407.16741v3
Importantly, OpenHands is not just a conceptual framework, but it also includes a comprehensive and immediately usable implementation of agents, environments, and evaluations

Computation and Language

https://arxiv.org/list/cs.CL/new
Prior work enables one-way, scholar-oriented translation from Akkadian to English, but offers no path in the reverse direction: non-specialist users cannot compose new content in cuneiform, and therefore remain passive consumers of ancient culture rather than active participants

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https://arxiv.org/html/2608.03063v1
Consider a shop registered under “clothing” that in fact sells jade via livestreams, luring buyers to pay by a QR code sent in private chat: suspicious wording, but not conclusive on its own

MinerU2.5: A Decoupled Vision-Language Model for Efficient High

https://arxiv.org/html/2509.22186v2
3 Iterative Mining via Inference Consistency 5 Evaluation 5

Efficient Audio Enhancement with a Differentiable Psychoacoustic Loss

https://arxiv.org/html/2608.02918v1
Miranda is also with LCTI, Télécom Paris, IP Paris, France

AgentScope 1.0: A Developer-Centric Framework for Building Agentic

https://arxiv.org/html/2508.16279v1
Following this trend, the focus of LLM-based agent frameworks has shifted from relying solely on intrinsic reasoning to empowering agents to perceive and interact with environments via an array of tools

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https://arxiv.org/html/2608.03077v1
Abstract Multi-domain machine translation (MDMT) requires more than fluent generation: it demands domain-sensitive translation decisions such as domain disambiguation, terminology control, and stylistic adaptation

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

https://arxiv.org/abs/2608.03883
Because no annotated training data were released for this first edition of the task, we relied on zero-shot experimentation, manual validation, and unsupervised or weakly guided retrieval pipelines

[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

[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

Information Retrieval

https://arxiv.org/list/cs.IR/recent
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 Information Retrieval Authors and titles for recent submissions Wed, 5 Aug 2026

Information Retrieval

https://arxiv.org/list/cs.IR/new
To handle it, KGD assigns them to separate parameter sets: a refreshable encoder owns behavioral knowledge, while a task learner reads contextualized encoder states through read-only cross-attention and writes task-specific geometry through Anchored Calibration Residual (ACR) orthogonal to the pretrained embedding

Evaluating OpenAI’s Privacy Filter: Cross-Lingual, Cross-Domain PII

https://arxiv.org/html/2608.02616v1
However, multilingual NER schemas (PER/ORG/LOC) do not cover contact information, financial identifiers, or structured PII types, making direct transfer non-trivial

1 Introduction

https://arxiv.org/html/2608.03486v1
Under suitable conditions, this auxiliary variable modulation facilitates recovery of the structural shocks even when the contemporaneous structural mapping is fully nonlinear and shocks do not enter additively

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https://arxiv.org/html/2608.02612v1
Our code and dataset are available at https://github

VibeVoice Technical Report

https://arxiv.org/html/2508.19205v1
Abstract This report presents VibeVoice, a novel model designed to synthesize long-form speech with multiple speakers by employing next-token diffusion SBW+ (24), which is a unified method for modeling continuous data by autoregressively generating latent vectors via diffusion

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https://arxiv.org/html/2608.02609v1
It is not a barrier between two living communities that might learn each other’s languages, but a one-way temporal asymmetry: ancient texts can be partially decoded for modern readers, but modern users have no productive channel into the ancient script

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https://arxiv.org/html/2608.03372v1
2 Closed-class checks transfer; open-class ones do not What is and is not being claimed

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https://arxiv.org/html/2607.22511v2
Because a machine-checked proof establishes only that a formal statement follows from its assumptions—not that the statement faithfully captures the intended scientific claim—the pipeline augments kernel verification with a statement audit that compares each formal theorem against the informal claim it is intended

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https://arxiv.org/html/2607.26245v1
We do not claim trading profitability—the central empirical finding is the opposite, and that negative result is published with the data that produced it

Solving Zebra Puzzles Using Constraint-Guided Multi-Agent Systems

https://arxiv.org/html/2407.03956v3
It must also encode additional constraints: the Football and Red houses occupy House 1 or House 3, respectively, and they must not be the same house

1 Introduction

https://arxiv.org/html/2403.08299v1
They often do not leverage all IDE capabilities such as invoking linters, compilers, or executing command-line operations, and consequently, developers still need to manually validate syntax and ensure the correctness of AI-generated code, execute the codebase, and inspect error logs

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https://arxiv.org/html/2608.00785v1
com Abstract Content discovery systems depend on relevance judgment for search quality evaluation, but human annotation faces inter-annotator disagreement and scaling costs