Hugging Face Trending Papers
LongWoF-Bench: Evaluating EvoMap Genes for Verifiable Long-Workflow Tasks
Read the original on Hugging Face Trending Papers →The Flow has not summarised this story yet — read it at Hugging Face Trending Papers.
Related stories
arXiv Computation and Language
Aug 25
LongWoF-Bench: Evaluating EvoMap Genes for Verifiable Long-Workflow Tasks
LongWoF-Bench is a new benchmark of 778 machine‑verifiable long‑workflow tasks spanning code generation, agent‑environment synthesis, mathematical reasoning, and rule following. The study shows that EvoMap Genes—structured representations of verifier‑confirmed execution trajectories—outperform the Skill baseline by 8.7–15.5 percentage points across seven models, and for Claude Opus they enable 39 additional task completions while cutting token consumption by 9.9%. The results demonstrate that verified execution experience can be externalized and reused, improving long‑workflow completion without repeatedly discovering new strategies.
arXiv AI
Oct 1
EngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses
EngramBench is a new benchmark designed to evaluate skill evolution in autonomous agents by focusing on genuine capability abstraction rather than solution copying. It includes 30 learning tasks and 13 unseen transfer tasks that require agents to manage complex, multi-hour development cycles with LLM‑simulated users. The study shows that while static skill banks cannot eliminate the need for precise code implementation, they effectively reduce redundant context and cut overall coding time by more than 55%.
arXiv AI
Jun 2
BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution
arXiv:2606. 01286v1 Announce Type: cross Abstract: The rapid progress of frontier large language models has led to widespread benchmark saturation, limiting the ability of existing datasets to differentiate model capabilities or provide useful training signal.
arXiv AI
Jun 12
Evoflux: Inference-Time Evolution of Executable Tool Workflows for Compact Agents
arXiv:2606. 12674v1 Announce Type: new Abstract: Compact language models (LMs) reduce cost, latency, and deployment risk for tool agents.
arXiv AI
Oct 15
SkillHorizon: Constructing Long-Horizon Agent Tasks through Skill Composition
arXiv:2610.14966v1 Announce Type: new Abstract: Long-horizon agents must complete workflows in which later activities depend on earlier outputs and changes to shared state. A key challenge for evalua...
arXiv Computation and Language
Sep 16
From Procedural Skills to Strategy Genes: Towards Experience-Driven Test-Time Evolution
arXiv:2604.15097v3 Announce Type: replace-cross Abstract: This beta technical report asks how reusable experience should be represented so that it can function as effective test-time control and as a...