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The read step processes all chunks in parallel, with each chunk-level read conditioned on the same global memory, thereby avoiding sequential memory overwrites that may discard earlier evidence and reducing inference latency through parallel chunk processing
from the top result below
https://arxiv.org/html/2608.03048v1
The read step processes all chunks in parallel, with each chunk-level read conditioned on the same global memory, thereby avoiding sequential memory overwrites that may discard earlier evidence and reducing inference latency through parallel chunk processing
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
https://arxiv.org/list/cs.AI/new
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https://arxiv.org/html/2501.13956v1
2 Knowledge Graph Construction
2.1 Episodes
2.2 Semantic Entities and Facts
2.2.1 Entities
2.2.2 Facts
2.2.3 Temporal Extraction and Edge Invalidation
2.3 Communities
3 Memory Retrieval
3.1 Search
3.2 Reranker
4 Experiments
4.1 Choice
https://arxiv.org/html/2407.16294v1
1 Introduction
The ideal that agent-based modelling (ABM) in social simulation strives to achieve, in many cases, is a true representation of the ‘society-of-agents’ under study, so that we may gain insight into (or even generate) surprising interactions, emergent behaviour, and some level of explainability in an
https://arxiv.org/html/2608.03504v1
Because many common digital advertising formats (such as “Top Picks,” “Recommended,” or “Featured” slots) primarily reallocate limited on-screen space rather than requiring substantial additional spending, improving the design of these advertisements may yield significant profit gains at relatively low
https://arxiv.org/html/2410.17799v2
Audio samples of dialogues generated by OmniFlatten can be found at this web site 111https://omniflatten
https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries
https://arxiv.org/list/cs.IR/new
For what to learn, conventional next-token prediction treats adjacency as dependency and may encode spurious transitions across unrelated sessions
https://arxiv.org/abs/2604.07181
Therefore, a policymaker seeking to maximize welfare may consider designing policies based on observed characteristics and estimated latent traits
https://arxiv.org/html/2608.02612v1
Users ask a meta-solver to formulate a BBO problem for their task, but they may not have an implemented objective function when they describe the task
https://arxiv.org/list/cs.SE/new
One system message may require valid JSON, a word limit, three citations, and a fixed tone at the same time
https://arxiv.org/html/2407.16741v3
When designing AI agents, we can also consider how human interacts with the world
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
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
IR)
Tue, 4 Aug 2026 (showing first 34 of 45 entries )
[17] arXiv:2608
https://arxiv.org/list/cs.CL/new
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/html/2608.01366v2
8 Per-Participant Phase-Averaged Cognitive Load
License: arXiv
https://arxiv.org/list/eess/new
comp-ph)
Designing an effective electromagnetic inverse-scattering solver requires faithful enforcement of nonlinear full-wave physics together with an expressive prior on the unknown permittivity contrast
https://arxiv.org/html/2607.29281v2
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