AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,629 papers
We propose a compact NISQ-compatible quantum transformer architecture for synthetic QNLP sequence modelling. The model preserves the autoregressive next-token interface of a classical transformer, but replaces attention and feed-forward sublayers with variational quantum encoder blocks, connector circuits, decoder bloc...
A metric interaction framework that models object-level and scene-level interactions in physical Cartesian space at a shared metric scale and improves diverse VLA and WAM baselines with a small number of additional parameters and training steps is introduced.
Large language models (LLMs) are increasingly deployed in applications involving interaction between agents, where their output plays a role in collective reasoning and decision-making processes. Despite significant research into the functioning of LLMs in such multi-agent systems, the processes of bias propagation in...
We study the problem of demonstration selection, which involves selecting a subset of examples for prepending to a query to a language model. This problem is closely related to in-context learning and language model inference. Since the inference cost of a transformer model scales quadratically with sequence length, th...
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This paper proposes and analyzes Comparison-based Preference Optimization (ComPO), a zeroth-order alignment method based on comparison oracles, and establishes a convergence guarantee for its basic offline scheme under smoothness, gradient sparsity, and compatibility between the oracle and a latent objective.
This work introduces physical rank consistency (PRC) to measure how well tokenization preserves local physical distance rankings after reconstruction, and presents ActionPiece, which preserves physical action relationships through joint supervision of representation learning and quantization.
These findings establish articulated rationales as a useful complement to behavioral and content signals, and demonstrate a practical role for MLLMs in scaling sparse human explanations into preference information that improves industrial recommendation.
Immigration is one of the most politically salient and emotionally charged issues in contemporary public life, shaping debates about national identity, belonging, economic change and social order. Social media platforms have become central arenas in which these debates unfold, allowing immigration-related claims, fears...
--- ## Alternative Titles 1. **The New Electricity: Artificial Intelligence as Protector of Future Welfare — An Analytical Study of AI Adoption in India** 2. **AI as Rakshak: Examining the Transformative Promise, Ethical Challenges, and Policy Imperatives of Artificial Intelligence in the Indian Context** 3. **From Thr...
The paper presents a novel large language model-based neighbourhood search method for production scheduling using discrete-event simulation (DES) as the modelling and evaluation engine. The combination of large language models (LLMs) and DES represents a relatively new area of research with significant potential. The c...
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22775771. Summary The authors tackle a real obstacle in interpretability: you can't compare SAE features across training checkpoints, because separately trained dictionaries assign...
We reproduce and extend FinRL-DeepSeek (Benhenda, 2025), a trading framework combining Proximal Policy Optimization (PPO) (Schulman et al., 2017), Conditional Value-at-Risk (CVaR) constraints (Rockafellar and Uryasev, 2000), and large language model (LLM) signals extracted from financial news. Using the Nasdaq-100 univ...
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A Blog post by Ai2 on Hugging Face
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