Skill Routing
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Related Articles from SNS
Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition
arXiv:2606.06893v1 Announce Type: new Abstract: Large language model agents increasingly rely on Skills to encode procedural knowledge, yet high-quality Skills remain costly to hand-write. This paper studies automatic Skill construction from heterogeneous interaction evidence, including demonstrations, agent trajectories, tool traces, and execution logs. We argue that trace-to-skill construction is not simple summarization tasks, because traces are fragmented, redundant, and may miss rare...
Skill Is Not Document: A Query-Conditional Benchmark and Two-Stage Retriever for LLM Agent Skill Routing
Announce Type: new Abstract: LLM agents complete complex tasks by composing multiple skills, and skill retrieval is a front-end stage for agents. Skill retrieval differs fundamentally from traditional document retrieval at the supervision level: top-K joint correctness depends not only on the semantic relevance of each individual query-skill pair, but also on whether the skills retrieved together can collaborate to fulfill the task under the given query. Such "skill compatibility" cannot be...
Skill Is Not Document: A Query-Conditional Benchmark and Two-Stage Retriever for LLM Agent Skill Routing
arXiv:2606.03565v2 Announce Type: replace Abstract: LLM agents complete complex tasks by composing multiple skills, and skill retrieval is a front-end stage for agents. Skill retrieval differs fundamentally from traditional document retrieval at the supervision level: top-K joint correctness depends not only on the semantic relevance of each individual query-skill pair, but also on whether the skills retrieved together can collaborate to fulfill the task under the given query. Such "skill...
Skill-Based Mixture-of-Experts: Adaptive Routing for Heterogeneous Reasoning via Inferred Skills
Announce Type: replace Abstract: Combining existing pre-trained LLMs is a promising approach for diverse reasoning tasks. However, task-level expert selection is often too coarse-grained, since different instances may require different expertise.
Channel Fracture: Three Instances of Cross-Boundary Silent Delivery Reliability Failures in Multi-Agent Systems
arXiv:2606.04896v3 Announce Type: replace Abstract: We report the discovery of channel fracture, a silent architectural failure in multi-agent systems where information routed across agent boundaries is silently blocked by invisible constraints. We present three instances in a production Hermes Agent deployment: (1) cron memory injection blocked by scheduler barriers; (2) cross-profile skill routing fractured by recursive directory traversal; (3) WebSocket delivery confirmation fallback...
MOSAIC: Efficient Mixture-of-Agent Scheduling via Adaptive Aggregation and Inference Concurrency
arXiv:2606.03014v1 Announce Type: new Abstract: Mixture-of-Agents (MoA) systems improve reasoning accuracy by routing each query to multiple expert LLMs and aggregating their outputs. Efficiently executing this workload on limited GPU resources has bottlenecks. Skill-based routing creates skewed expert demand, and combining instruction-tuned LLMs with long-reasoning models results in extreme variability in generation lengths.
Ranking college football's top 100 newcomers for t...
If the upcoming 2026 college football season is anything like its predecessor, transfer quarterbacks and top freshmen will be crucial for many College Football Playoff runs. And by now, with less than 100 days until the start of the season, we can assess rosters and what players did during spring practice with their new teams. While we have analyzed the top newcomer for each Power 4 team, these rankings are regardless of teams.
Agentic Neuro-Symbolic Planning and Commissioning for Human-in-the-Loop Industrial Robotics with Digital Twins
arXiv:2606.08214v1 Announce Type: new Abstract: Flexible robotic automation requires systems that interpret operator intent, verify physical feasibility, and recover from execution failures across both the planning and execution stages. This paper proposes an agentic neuro-symbolic framework for human-in-the-loop industrial robotics, in which LLMs are used for tasks that require language understanding or contextual reasoning, while all verification, sequencing, and execution remain...
One third say 'not worth the money' in new student loan update
One third say 'not worth the money' in new student loan update An inquiry into England's student loan system has been launched by MPs, as new survey data shows a third of people now believe a university education is not worth the time and financial commitment required A new survey revealing that one in three people doubt the value of a university degree comes as "not surprising" to experts. MPs have launched an investigation into England's student loan system, gathering testimony from...
PHASER: Phase-Aware and Semantic Experience Replay for Vision-Language-Action Models
Announce Type: new Abstract: Vision-Language-Action (VLA) models have achieved remarkable success in language-conditioned robotic manipulation. However, deploying these models in open-ended environments requires continuously acquiring novel skills, a process that inevitably triggers severe catastrophic forgetting of previously learned behaviors. While experience replay (ER) serves as a standard mitigating strategy, naive uniform sampling fundamentally misaligns with the temporal...