#architecture

9 curated events

papersTODAY 04:00 UTC

Bypass Observation: Read-Only Layer-Wise Semantic Extraction for LLMs

A new arXiv paper proposes Bypass Observation, an architecture that adds read-only observation heads to selected Transformer layers so internal hidden states can be inspected without altering the model's behavior. The approach aims to bridge the gap between the high-dimensional reasoning space of large language models and the text-only outputs users normally see. It is presented as a conceptual design for non-intrusive semantic extraction.

interpretability/llm/research/architecture

papersTODAY 04:00 UTC

arXiv Paper Proposes Contract-Based Architecture for Enterprise Agent Runtimes

A new arXiv paper outlines an architecture for enterprise agentic systems built around explicit responsibility contracts, defining roles such as Skill, Harness, Scaffold, and an external data substrate. The authors argue this contract-centered framing makes it easier to scale and manage agents as capabilities, compute capacity, and governed data change independently. The work emphasizes cost-aware design for coordinating these components.

agents/arxiv/enterprise/architecture

papersTODAY 04:00 UTC

Paper proposes separating persona from execution in auditable LLM agents

A new arXiv paper argues that governed organizations need LLM agents whose persona — prompts, tone and self-presentation — can change freely while their stateful work remains traceable. It notes that a single trust domain cannot satisfy both requirements at once, and proposes a persona-execution separation pattern as an architectural fix. The approach is framed around execution auditability for enterprise deployments.

agents/llm-agents/audit/architecture

papersTODAY 04:00 UTC

Perfect-Reconstruction View of AddUNet and a Residual Full-Rate Architecture

A new arXiv paper reframes the AddUNet model through the lens of perfect reconstruction and describes how it can operate at full rate. The authors introduce a residual full-rate perfect-reconstruction design aimed at task-directed representation learning, building on the architecture's survivor-skip structure. The work is theoretical and architectural rather than a released product or benchmark result.

research/architecture/representation-learning/arxiv

papersSEP 10 04:00 UTC

Study challenges the narrow-wide-narrow FFN convention in Transformer language models

An arXiv research paper questions why dense Transformers almost universally place most of their non-embedding parameters in narrow-wide-narrow feed-forward networks. Drawing on theoretical and empirical evidence, the authors explore an alternative wide-narrow-wide (hourglass) residual design for these blocks. The work is cross-listed across the cs.AI, cs.CL, and cs.LG categories on arXiv.

transformers/architecture/research/efficiency

papersSEP 10 04:00 UTC

New Relation mechanism decouples relation formation from flow allocation in token mixing

A revised arXiv paper in machine learning introduces Relation, a token-mixing mechanism that splits an operation standard attention fuses into a single score-to-flow step. The method first organizes pairwise evidence into explicit Self and Exchange relations and then allocates information flow across them. The authors position this as an alternative to dominant attention-based token mixing in sequence models.

attention/architecture/deep-learning/transformers

papersSEP 10 04:00 UTC

New Research Outlines an Operational Architecture for Cognitive Digital Twins

A newly posted arXiv paper proposes an operational architecture for cognitive digital twins, which extend traditional digital twins by adding reasoning and knowledge-driven behavior. Rather than simply mirroring the state of a physical system, the framework is designed to let twins pursue tasks and improve their own cognitive capabilities over time. The work positions this shift as the next stage in the evolution of digital twin systems.

digital-twins/architecture/self-improving/research

papersSEP 10 04:00 UTC

A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Model

A paper on arXiv lays out a taxonomy of the main architecture options available for building agent systems powered by foundation models. It pairs this classification with a decision model designed to help practitioners analyze trade-offs and select appropriate designs when developing or operating such systems.

agents/research/architecture/foundation-models

papersSEP 10 04:00 UTC

SymbolicLight V2 paper proposes hybrid neuromorphic architecture for low-energy language inference

A new arXiv paper presents SymbolicLight V2, a language model architecture that combines sparse, event-driven computation with conventional continuous-state processing. It extends the earlier spike-gated design by adding graded signed events at additional projection layers along with a softmax-free local attention mechanism. The work targets reduced energy consumption during language inference.

neuromorphic/energy-efficiency/inference/architecture