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This study synthesizes adjacent research and introduces Enactive AI as a conceptual framework for enterprise and industry reasoning, site-level decision support, and execution feedback
from the top result below
https://arxiv.org/list/cs.AI/new
Existing tool-use agents typically rely on LLMs to infer tool compositions from textual descriptions, which can lead to inefficient exploration and unreliab
https://arxiv.org/list/cs.SE/new
PL)
Glob patterns, a domain-specific language for structured string matching, are a foundational yet understudied component of modern software development embedded in everything from build scripts and configuration files to web server routes
https://arxiv.org/list/cs.CR/new
We also show that coarse-to-fine label selection can create near-perfect measured correlation without learned dependence
https://arxiv.org/list/cs.IT/new
IT)
Suppressive interference, high-dynamic motion of the receiving platform, and carrier-phase RTK lead satellite navigation to one fundamental question: when the receiver actively participates in observation formation through its array geometry, channel states, weights, and signal-processing rules, how can the
https://arxiv.org/html/2609.03159v1
Whalen (NASA Postdoctoral Fellow (ORAU); NASA/GSFC)
1 Executive Summary
We must create superb X-ray images to understand the detailed physical processes behind some of the most powerful astronomical objects
https://arxiv.org/list/cs.CL/new
Users can read ancient tablets (Akkadian to English) and compose new messages as cuneiform clay tablets (English to Akkadian to cuneiform to rendered tablet)
https://arxiv.org/html/2608.03573v1
In contrast, parameter updates induced by RL across different tasks are approximately orthogonal and can therefore coexist, enabling multi-stage RL to stably improve performance across tasks over stages
https://arxiv.org/list/math/new
It is natural to expect that if many pairs $(x_i,x_j)$ lie at distance close to $1$ from each other, then some clustering phenomenon must occur, implying that a significant number of these pairs are also very close to each other
https://arxiv.org/list/cs.CV/new
To address this limitation, we propose Hunyuan3D-Buffalo 1
https://arxiv.org/abs/2608.02122
Although Dynamic Voltage and Frequency Scaling (DVFS) provides an effective mechanism for reducing GPU energy consumption, existing runtime systems decouple DVFS from task placement and inter-GPU communication, focus on single-GPU execution, or cannot adapt frequency to task granularity and runtime contention in multi
https://arxiv.org/list/eess.SP/new
The three channels are integrated at a common input port via a T-junction, with connecting transmission line stubs dimensioned to enforce high inter-channel isolation
https://arxiv.org/html/2608.02617v1
In this setting, small factual errors, omitted red flags, or overly confident phrasing can lead to significant downstream harm
https://arxiv.org/html/2608.00458v1
To address these challenges, we propose BANDMAS, a multi-agent collaboration framework that models inter-agent communications as task-oriented traffic, which enables efficient transmission via causality-inspired replay valuation
https://arxiv.org/html/2608.03233v1
Our findings highlight a concerning issue of domain homogeneity, a prevalent tendency for LLMs to generate analogies from a narrow set of target domains, limiting both inter-query and intra-model diversity
https://arxiv.org/html/2608.03048v1
for large language models, as recent recurrent-memory approaches face two inherent challenges: sequential chunk-wise updates can overwrite early critical evidence with later irrelevant content, and serial inter-chunk dependencies limit parallelism and cause latency to increase with context length
https://arxiv.org/html/2511.06451v1
From selective scan to a risk-neutral operator layer
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/2608.03529v1
There, the annotation space is known in advance, and measuring Inter-Rater Reliability (IRR) on the resulting codified annotations Cohen (1960); Scott (1955); Fleiss (1971) is standard procedure to enable insights into their reliability and quality Artstein and Poesio (2008); Hanegraaf et al
https://arxiv.org/html/2410.05779v3
However, existing RAG systems have significant limitations, including reliance on flat data representations and inadequate contextual awareness, which can lead to fragmented answers that fail to capture complex inter-dependencies
https://arxiv.org/html/2508.20108v2
How can we address distribution shifts in stock price data to improve stock price prediction accuracy
https://arxiv.org/list/cs.NA/new
Nazarov, A new approach to the reaction-diffusion systems modelling, Vestn
https://arxiv.org/html/2608.00426v1
In MAS, poisoned items can instead propagate from private to shared memory and reach agents that were never directly targeted
https://arxiv.org/html/2407.14571v1
As the raw multi-variate time series data generated by DataStorm-FE can be both large and complicated to parse, and users may be domain experts and not necessarily data scientists, it is critical that data exploration and analysis be accessible:
•
Consequently, DataStorm-EM provides intuitive and easy-to-use
https://arxiv.org/html/2608.03067v1
4 Statistical analysis
5 Results
Inter-rater reliability for human ratings
https://arxiv.org/html/2608.00648v1
In these scenarios, heterogeneous agents and complex task constraints require efficient inter-agent coordination to improve execution efficiency
https://arxiv.org/html/2407.19144v1/
These malfunctions decrease the team’s ability to accomplish assigned task(s), especially if they occur after the learning algorithms have already converged onto a collaborative strategy
https://arxiv.org/html/2608.03655v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.03014v1
In particular, multi-user MIMO (MU-MIMO) enables a base station (BS) to serve multiple users simultaneously on the same time–frequency resources, but doing so reliably requires precoding and receiver combining that both provide array gain and actively control inter-user interference [15]
https://arxiv.org/list/cs.DC/new
The main question of interest is how close one can remain to the desired palette size of $\Delta+1$ while computing, in few distributed rounds, a coloring whose frequencies are close to $\sigma$
https://arxiv.org/html/2608.03044v1
edu
Abstract
Large language models are increasingly used to simulate human opinions, but prior work reports conflicting results: some studies find promising alignment with human survey data, while others find persona collapse and weak demographic sensitivity