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18 result(s) for “okapi bm25 site hotchips pp site github com site via di unit it site drafts css site:arxiv.org” · 598 ms

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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

Report GitHub Issue

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

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

Computation and Language

https://arxiv.org/list/cs.CL/new
With the interaction history, it co-generates ground truth over six recall, reasoning, and trustworthiness evaluation dimensions

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

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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

Internalizing Academic Writing Workflows for Introduction Generation via

https://arxiv.org/html/2608.03138v1
since it requires coordinating background, gap identification, method and contribution within a coherent narrative

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

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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

Asking Questions the Right Way: A Multi-Agent Conversational System for

https://arxiv.org/html/2608.01366v2
com Affiliation: Department of Design and Manufacturing, Indian Institute of Science (IISc) , Bangalore , India , Srinidhi Ranjini Girish email: srinidhirgirish@gmail

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

[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
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

Speculative Correction: Draft-then-Refine Decoding for Diffusion

https://arxiv.org/html/2608.02625v1
1-mini drafts a full response, and LLaDA2

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

1 Introduction

https://arxiv.org/html/2504.19413v1
ai/research 1 Introduction Human memory is a foundation of intelligence—it shapes our identity, guides decision-making, and enables us to learn, adapt, and form meaningful relationships (Craik and Jennings, 1992)