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18 result(s) for “okapi bm25 site hotchips pp site terms com pp site vigna di unit it site:arxiv.org” · 759 ms

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Did you mean okapi bm25 site hotchips pp site terms com pp site vina di unit it site:arxiv.org?

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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
Instead, it falls on local, personal agents to effectively and safely maintain/utilize such dense person-person (PP) and person-agent (PA) interaction histories

Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
An LETF must trade in the direction of the day’s move at a close that also measures it, so its demand rises in price, and arbitrageurs buying ahead of it enlarge the order by trading at the print, then unload into what they manufactured

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
However, it is not obvious how a researcher should direct their efforts to produce evidence toward such objectives

Effort-Centric Fairness in Lending Decisions

https://arxiv.org/html/2607.28847v1
Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML? Report Issue Back to

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

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

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

Computation and Language

https://arxiv.org/list/cs.CL/new
2 pp, exceeding MemSearch reader scaling (+10

1 Introduction

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

Multi-Currency AMMs for Decentralized FOREX Markets: Feasibility

https://arxiv.org/html/2607.26405v1
It then formulates the system-level problem of partitioning currencies into multi-currency pools, which is solved using a hierarchical agglomerative clustering algorithm

Mathematics

https://arxiv.org/list/math/new
up to 2000 entries per page: fewer | more | all New submissions (showing 219 of 219 entries) [1] arXiv:2608

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

Distributed Instruments for Planetary Surface Science: Scientific

https://arxiv.org/html/2407.01757v1
It is natural to ask whether this lack of adoption is driven by low potential to address high-priority questions in planetary science; immature technology; or both

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of

https://arxiv.org/html/2608.03573v1
org perpetual non-exclusive license arXiv:2608

[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

[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
IR) Tue, 4 Aug 2026 (showing first 34 of 45 entries ) [17] arXiv:2608