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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
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
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
https://arxiv.org/html/2608.03048v1
6 million tokens and find that it outperforms the recurrent-memory baseline by +6
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
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
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
https://arxiv.org/html/2608.02918v1
Miranda is also with LCTI, Télécom Paris, IP Paris, France
https://arxiv.org/html/2608.03011v1
Built upon the flow-matching-based F5-TTS, it uses a speech-environment separation module to decompose environmental speech into speech, noise, and reverberation components, which are injected into the Diffusion Transformer for environment-aware generation
https://arxiv.org/html/2510.03215v2
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https://arxiv.org/html/2608.03063v1
Compared with the production DeepSeek-based LLM baseline, it improves screening precision from 92
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
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
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/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
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Information Retrieval
Authors and titles for recent submissions
Wed, 5 Aug 2026
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
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
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
https://arxiv.org/html/2608.03372v1
2 Closed-class checks transfer; open-class ones do not
What is and is not being claimed
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
https://arxiv.org/html/2509.22186v2
In the second stage, guided by the global layout, it performs targeted content recognition on native-resolution crops extracted from the original image, preserving fine-grained details in dense text, complex formulas, and tables
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
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
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
https://arxiv.org/html/2608.02612v1
Our code and dataset are available at https://github
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
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
https://arxiv.org/html/2407.17789v2
Last but not least, we provide a web-based interface for conveniently monitoring and managing a large number of agents that might deploy across multiple devices
https://arxiv.org/html/2608.03446v1
To our knowledge, no prior work has inspected the impact of CLA scores on translation performance
https://arxiv.org/html/2508.16279v1
AgentScope adopts the ReAct paradigm as the primary and recommended agent architecture, as it provides a simple yet effective paradigm for agent-environment interaction