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from the top result below

Computation and Language

https://arxiv.org/list/cs.CL/new
Recent studies have therefore examined how to automatically derive optimization problems from natural-language descriptions, but existing benchmarks focus on settings where objectives and constraints can be written explicitly as mathematical expressions

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

Computer Vision and Pattern Recognition

https://arxiv.org/list/cs.CV/new
CV) Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing

On the Diversity of Analogy Making in Large Language Models

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

arXiv is now an independent nonprofit! Learn more ×

https://arxiv.org/html/2609.03159v1
We believe we have done this and have progressed a mission concept to a feasible architecture for further study to expand the possibilities around today’s future X-ray missions

1 Introduction

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

Collaborative Adaptation for Recovery from Unforeseen Malfunctions in

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

Report GitHub Issue

https://arxiv.org/html/2608.00458v1
Our intuition is to treat generated inter-agent text as application traffic whose contents have different task values, rather than as an indivisible conversation history

Report GitHub Issue

https://arxiv.org/html/2608.02613v1
A million-token cloud context window does not help here, as it requires off-device upload, which privacy-sensitive personal memory management is meant to avoid

Very Large-Scale Multi-Agent Simulation in AgentScope

https://arxiv.org/html/2407.17789v2
org perpetual non-exclusive license arXiv:2407

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

https://arxiv.org/html/2608.01366v2
org perpetual non-exclusive license arXiv:2608

Preferred, Not Safer: Pairwise Preference Is a Poor Proxy for Clinical

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

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

Activation-Guided Neuron Intervention to Induce Alzheimer’s-Related

https://arxiv.org/html/2608.03067v1
Beyond their use as predictors, pretrained language models have also become tools for examining how linguistic information is organized in internal representations that can support AD prediction (Balagopalan et al

MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
In these scenarios, heterogeneous agents and complex task constraints require efficient inter-agent coordination to improve execution efficiency

Emulate or Estimate? The Divergent Strengths of Base and Post-Trained

https://arxiv.org/html/2608.03044v1
(2025) concluded that sociodemographic prompting does not reliably shift model outputs toward target demographics

[2006.02833] An Automated Implementation of Hybrid Cloud for Performance

https://arxiv.org/abs/2006.02833
This model of applications deployment is called cloud bursting that allows data-intensive applications especially distributed database systems to have the benefit of both private and public clouds

Numerical Analysis

https://arxiv.org/list/cs.NA/new
Nazarov, A new approach to the reaction-diffusion systems modelling, Vestn

Consensus Measures for Unstructured Biomedical Text Annotations

https://arxiv.org/html/2608.03529v1
Because the target concepts are not known in advance, annotators prefer open-ended labels, whose agreement is hard to quantify

Signal Processing

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

Distributed, Parallel, and Cluster Computing

https://arxiv.org/list/cs.DC/new
DC) The artificial intelligence industry has constructed a USD 300 billion centralized data center infrastructure to serve a workload, large language model inference, that does not architecturally require centralization

Process-Knowledge-Embedded Safe DRL for Real-Time Dispatch of Process

https://arxiv.org/html/2608.03149v1
I Introduction Real-time dispatch of steelmaking process loads (SPLs) in response to fluctuations in local renewable generation and grid electricity prices is essential for increasing on-site renewable energy utilization and reducing electricity procurement costs in industrial microgrids [TOP1, TOP4]

Information Theory

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

Report GitHub Issue

https://arxiv.org/html/2608.00426v1
org perpetual non-exclusive license arXiv:2608

[2608.02122] DEFT: Joint Task Placement and DVFS for Energy-Efficient

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

Condensed Matter

https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries

1 Introduction

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

Software Engineering

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

Matching-Driven Deep Reinforcement Learning for Energy-Efficient

https://arxiv.org/html/2407.13076v1
Such inter-SF interference may increase the possibility of packet loss when the signal-to-interference ratio (SIR) is below a specific threshold [12]

United We Stand: Decentralized Multi-Agent Planning With Attrition

https://arxiv.org/html/2407.08254v2
These agents can communicate and coordinate with each other, either directly or indirectly, to solve complex tasks that are beyond a single agent’s capabilities