Trinity-Large-Thinking by Arcee
The first open model as performant as Opus 4.6, 96% cheaper Discussion | Link
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ROSClaw: A Hierarchical Semantic-Physical Framework for Heterogeneous Multi-Agent Collaboration
arXiv:2604.04664v1 Announce Type: cross Abstract: The integration of large language models (LLMs) with embodied agents has improved high-level reasoning capabilities; however, a critical gap remains between semantic understanding and physical execution. While vision-language-action (VLA) and vision-language-navigation (VLN) systems enable robots to perform manipulation and navigation tasks from natural language instructions, they still struggle with long-horizon sequential and temporally structured tasks. Existing frameworks typically adopt modular pipelines for data collection, skill training, and policy deployment, resulting in high costs in experimental validation and policy optimization. To address these limitations, we propose ROSClaw, an agent framework for heterogeneous robots that
How MCP Servers Handle Authentication (And Where They Get It Wrong)
How MCP Servers Handle Authentication (And Where They Get It Wrong) Authentication is one of the most frequently mishandled aspects of MCP server design. I've reviewed dozens of open-source servers and the same mistakes appear repeatedly. Here's what correct MCP authentication looks like — and the patterns that create security vulnerabilities. The Authentication Problem Space MCP servers face three distinct authentication challenges: Authenticating callers — verifying that the Claude Code session connecting to your server is authorized Authenticating to external services — securely using API keys to call third-party APIs Authorizing tool calls — ensuring specific tools can only be called with sufficient permissions Most tutorials only address #2, and often do it wrong. Problem 1: MCP Serve
Modelling and Analysis of Supply Chains using Product Time Petri Nets
arXiv:2604.04544v1 Announce Type: cross Abstract: Supply chains involve geographically distributed manufacturing and assembly sites that must be coordinated under strict timing and resource constraints. While many existing approaches rely on Colored Petri Nets to model material flows, this work focuses on the temporal feasibility of supply chain processes. We propose a modular modelling approach based on Product Time Petri Nets (PTPNs), where each subsystem is represented independently and the global behaviour emerges through synchronised transition labels. A key feature of the model is the explicit representation of the supply chain manager as a critical shared and mobile resource, whose availability directly impacts system feasibility. We analyse how timing constraints and managerial cap
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ROSClaw: A Hierarchical Semantic-Physical Framework for Heterogeneous Multi-Agent Collaboration
arXiv:2604.04664v1 Announce Type: cross Abstract: The integration of large language models (LLMs) with embodied agents has improved high-level reasoning capabilities; however, a critical gap remains between semantic understanding and physical execution. While vision-language-action (VLA) and vision-language-navigation (VLN) systems enable robots to perform manipulation and navigation tasks from natural language instructions, they still struggle with long-horizon sequential and temporally structured tasks. Existing frameworks typically adopt modular pipelines for data collection, skill training, and policy deployment, resulting in high costs in experimental validation and policy optimization. To address these limitations, we propose ROSClaw, an agent framework for heterogeneous robots that
Soft Tournament Equilibrium
arXiv:2604.04328v1 Announce Type: cross Abstract: The evaluation of general-purpose artificial agents, particularly those based on large language models, presents a significant challenge due to the non-transitive nature of their interactions. When agent A defeats B, B defeats C, and C defeats A, traditional ranking methods that force a linear ordering can be misleading and unstable. We argue that for such cyclic domains, the fundamental object of evaluation should not be a ranking but a set-valued core, as conceptualized in classical tournament theory. This paper introduces Soft Tournament Equilibrium (STE), a differentiable framework for learning and computing set-valued tournament solutions directly from pairwise comparison data. STE first learns a probabilistic tournament model, potenti
Why Your Claude Code Sessions Keep Losing Context (And How to Fix It)
Why Your Claude Code Sessions Keep Losing Context (And How to Fix It) Context loss is the most common productivity killer in long Claude Code sessions. You start with a clear plan, 45 minutes in Claude has forgotten key decisions, and you're re-explaining things you already covered. Here's what's actually happening and the structural fixes that eliminate it. What Causes Context Loss Claude Code has a finite context window. In long sessions: Early files get compressed — the model's effective attention on files read 30 minutes ago degrades Implicit decisions aren't retained — if you said "use Zod for validation" in conversation, that can drift out of focus Error history gets lost — Claude stops connecting current errors to past ones you already fixed This isn't a bug. It's how transformer mo
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