Papersby GlyphStarHarness: Evolving Harnesses with Stratified Search for Enterprise Environments research paper by ServiceNow, 2026
ServiceNow · Retrieval and data · Aug 25, 2026 · 3 citations · 41 upvotes · unverified
What it shows
StarHarness evolves fixed-weight agent harnesses via stratified task pools and hidden selection to improve enterprise tool-use performance and cross-model transfer.
By Esakkivel Esakkiraja, Denis Akhiyarov, Vikas Yadav and 4 more · arXiv 2608.24804 · PDF
UnverifiedHugging Face's summary; not yet checked by hand.
More from ServiceNow
All 21Apriel Voice 27B Preview: An Open Model for Speech, Reasoning, and Tool UseApriel Voice 27B is an open AI model that directly processes spoken speech to converse, reason, and use external tools.
ServiceNow37 upvotesRead →AgentJudgeBench: A Multi-Difficulty Benchmark for Evaluating LLM Judges on Agentic Tool-CallingAgentJudgeBench reveals that LLM judges face structural reliability limits on dependency-driven agentic tool-calling workflows, with alignment degrading by difficulty and ground-truth exposure yielding mixed effects.ServiceNow4 citations19 upvotesRead →SynthDocBench: Controlled Benchmark for Long-Context Visual Document UnderstandingSynthDocBench is a synthetic long-context visual document benchmark that isolates failure modes in vision-language models, revealing sharp length degradation, positional sensitivity, and chart comprehension breakdowns.ServiceNow1 citations68 upvotesRead →EVA-Bench: A New End-to-end Framework for Evaluating Voice AgentsEVA-Bench presents a comprehensive evaluation framework for voice agents that simulates realistic conversations and measures performance across multiple voice-specific failure modes using novel accuracy and experience metrics.ServiceNow20 citations77 upvotesRead →Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer DynamicsEnterprise discovery agents that read system configuration at runtime outperform traditional world models in configurable environments where dynamics change over time.ServiceNow2 citations65 upvotesRead →Apriel-Reasoner: RL Post-Training for General-Purpose and Efficient ReasoningApriel-Reasoner is a 15B-parameter language model trained with reproducible multi-domain reinforcement learning to improve reasoning efficiency and accuracy across diverse tasks while reducing inference costs.ServiceNow12 upvotesRead →Therefore I am. I ThinkReasoning models appear to encode action choices before beginning textual deliberation, as evidenced by early decision detection and activation steering effects.ServiceNow2 citations31 upvotesRead →Terminal Agents Suffice for Enterprise AutomationSimple terminal-based coding agents using programmatic interfaces and foundation models can effectively perform enterprise tasks comparable to or better than complex tool-augmented agents.ServiceNow6 citations98 upvotesRead →
Other retrieval and data papers
TopicBLOOM: A 176B-Parameter Open-Access Multilingual Language ModelBLOOM, a 176B-parameter open-access language model, achieves competitive performance on various benchmarks and is released publicly with a Responsible AI License.
Hugging Face3,165 citations41 upvotesRead →From Local to Global: A Graph RAG Approach to Query-Focused SummarizationGraphRAG builds a knowledge graph of a document set so a model can answer questions about the whole collection.
Microsoft2,561 citations7 upvotesRead →DINOv3DINOv3, a self-supervised learning model, achieves superior performance across various vision tasks by scaling datasets and models, addressing dense feature degradation, and enhancing flexibility with post-hoc strategies.
Meta1,932 citations320 upvotesRead →Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and RankingThe Qwen3-VL-Embedding and Qwen3-VL-Reranker models form an end-to-end multimodal search pipeline, leveraging multi-stage training and cross-attention mechanisms to achieve high-precision retrieval across diverse modalities.
Alibaba (Qwen)315 citations59 upvotesRead →DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic DataGenerating extensive Lean 4 proof data from mathematical competition problems improved DeepSeekMath 7B's theorem-proving capabilities over GPT-4 and other methods.
DeepSeek284 citations47 upvotesRead →Aya Dataset: An Open-Access Collection for Multilingual Instruction TuningThe initiative builds a human-curated instruction-following dataset spanning 65 languages and creates the largest multilingual collection of instruction-following instances through templating and translating existing datasets across 114 languages, contributing datasets and platforms for participatory research.
Cohere253 citations57 upvotesRead →
About this paper
- Venue
- arXiv.org
- Citations
- 3, 0 influential · Semantic Scholar
- Upvotes
- 41 · Hugging Face
- Lab
- ServiceNow · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf
Changes
Citations rose from 2 to 3.
Citations rose from 1 to 2.
A first count of 0 influential citations.
A first count of 1 citations.
Found by the weekly Hugging Face scan; not yet checked by hand.