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30 result(s) for “okapi bm25 site terms com pp site github com site going in site xiang me site:arxiv.org” of 74 matched · 1195 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
https://arxiv.org/html/2608.02613v1
7 Extrapolation across readers for cache-replay backends
TTFT rows in Table 3
https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands
Slack http://bit
https://arxiv.org/list/cs.AI/new
In practice, many field descriptions remain ambiguous or incomplete, as much of the essential context (e
https://arxiv.org/html/2607.22511v2
We present CausalForge, a framework for automated theoretical research in causal inference grounded in the Lean proof assistant
https://arxiv.org/html/2608.03048v1
com/JetAstra/PI-Mem
Introduction
The ability to reason over long contexts is increasingly important for large language models (LLMs), supporting applications such as long-document question answering (Gemini Team 2025; Yang et al
https://arxiv.org/html/2608.03154v1
com/COMBINI-Hub/Multi_Agent_Relation_Extraction
https://arxiv.org/html/2508.19205v1
com/microsoft/VibeVoice
Hugging Face: microsoft/VibeVoice
Demo: aka
https://arxiv.org/html/2509.22186v2
com/opendatalab/MinerU \metadata[Model:]https://huggingface
https://arxiv.org/html/2407.17789v2
com/modelscope/agentscope/tree/main/examples/paper_large_scale_simulation to inspire further research and development in large-scale multi-agent simulations
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/list/cs.CL/new
LG)
Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, leaving a 4,000-year cultural barrier that existing NLP tools have only partially addressed
https://arxiv.org/html/2608.00426v1
Memory-link poisoning yields ASR@3 above 75% in two gemma-4-31B settings
https://arxiv.org/html/2608.03099v1
In other systems, it directly conditions the action policy (Zitkovich et al
https://arxiv.org/html/2608.03655v1
Experiments on CNN/DailyMail, Multi-News, FaithBench, and TofuEval show consistent improvements in factuality and source-grounding metrics, especially for multi-document summarization, at the cost of lower reference-overlap scores
https://arxiv.org/html/2506.01844v1
While complementary in terms of modalities, such advances in developing multi-modal foundation models stem from (i) the adoption of scalable architectures, such as the Transformer (Vaswani, 2017) and (ii) internet-scale training datasets
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/html/2608.03077v1
Large reasoning models (LRMs) make such decisions explicit through intermediate translation steps, but our analysis across 15 domains and four translation directions shows that this explicit reasoning is double-edged: it improves long-form and high-difficulty translation, yet often drifts in terminology-intensive and
https://arxiv.org/pdf/2101.00190
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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/html/2410.05779v3
com Both Chao Huang and Yanhua Yu are corresponding authors
https://arxiv.org/html/2407.02518v2
com
Abstract
Large language models (LLMs) for code are typically trained to align with natural language instructions to closely follow their intentions and requirements
https://arxiv.org/html/2608.02665v1
We instantiate this in safety—a high-stakes setting with no gold label to average toward—treating single canonical, English, harmful prompts as the instrument under test
https://arxiv.org/list/math.ST/2024-03
05251 [pdf, html, other]
Title: Errors due to departure from independence in multivariate Weibull distributions
Subarna Bhattacharjee, Aninda K
https://arxiv.org/html/2508.16279v1
In line with such an evolution, AgentScope introduces major improvements in a new version (1
https://arxiv.org/list/cs.CV/2025-09
00131 [pdf, html, other]
Title: Self-supervised large-scale kidney abnormality detection in drug safety assessment studies
Ivan Slootweg, Natalia P
https://arxiv.org/list/cs.DC/2018-11
Springer Communications in Computer and Information Science, vol 790
Subjects: Distributed, Parallel, and Cluster Computing (cs
https://arxiv.org/list/astro-ph.IM/2024-01
The code developed to demonstrate the first working principles of the technique as introduced in this paper is released through a Python package called SIXSA (Simulation-based Inference for X-ray Spectral Analysis) available from GitHub at this https URL
Subjects: Instrumentation and Methods for Astrophysics (astro
https://arxiv.org/list/cs.AI/recent
03744 [pdf, html, other]
Title: Agents Catching Agents: Shortcut Cascades and Benchmark Gaming in Clinical Multi-Agent Systems
Sebastián Andrés Cajas Ordóñez, Agastya Munnangi, Aldo Marzullo, Felipe Ocampo Osorio, Quang Bui, Mohammad Shahin, Armaan Grewal, Emmanuel Paul Kwesiga, Anqi Peter Li, Josephine Nanyonjo
https://arxiv.org/list/cs.CV/2025-03
GitHub repository: this https URL
Subjects: Computer Vision and Pattern Recognition (cs