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- Parent WI: https://github.com/GenCr-ft/gcs-core-governance/issues/92
- Architecture decision: Option B (2026-06-26) — agent-context/ new top-level folder
Schemas Data Models
Proposed ...
Summary
The install flow should let the user choose which AI assistant(s) the repo should be set up for — and offer an explicit
** all assistants at once ** option — instead of silently auto-detecting ...
Auditing Framing-Sensitive Behavioral Instability in Large Language Models for Mental Health Interactions
Authors: Abla Bedoui, Ashley L. Greene, Mohammed Cherkaoui Published: 2026-06-25 Categories: cs.CL, ...
arxiv:cs.AI
arxiv:cs.CL
ReaORE: Reasoning-Guided Progressive Open Relation Extraction Empowered by Large Reasoning Models
Authors: Xin Lin, Liang Zhang, Guoqi Ma, Hongyao Tu, Jinsong Su Published: 2026-06-25 Categories: cs.CL, ...
arxiv:cs.AI
arxiv:cs.CL
Semantic Early-Stopping for Iterative LLM Agent Loops
Authors: Sahil Shrivastava Published: 2026-06-25 Categories: cs.AI, cs.LG, cs.MA
Links: abs | pdf
Abstract
Multi-agent large language model (LLM) ...
arxiv:cs.AI
arxiv:cs.LG
arxiv:cs.MA
License Name
WolfStack Software Licence
License Homepage URL https://github.com/wolfsoftwaresystemsltd/WolfStack/blob/master/LICENSE
new-license
NuclearQAv2: A Structured Benchmark for Evaluating Domain-Science Competence in Large Language Models
Authors: Henry Shaowu Yuchi, Michal Kucer, Benjamin H. Sims, Selma Peterson, Emily Taylor Published: ...
arxiv:cs.AI
arxiv:cs.CL
Application of LLMs to Threat Assessment of Foreign Peacekeeping Missions
Authors: Gerhard Backfried, Christian Schmidt, Diego Pilutti, Michael Suker Published: 2026-06-25 Categories: cs.CR,
cs.AI
Links: ...
arxiv:cs.AI
arxiv:cs.CR
Joint Learning of Experiential Rules and Policies for Large Language Model Agents
Authors: Shicheng Ye, Chao Yu Published: 2026-06-25 Categories: cs.AI
Links: abs | pdf
Abstract
For LLM agents in multi-step ...
arxiv:cs.AI
Problem Statement
Sudolife users can link a Strava account, but Sudolife does not yet import activity history. That blocks future training
insights because the application has no trusted, normalized activity ...
ready-for-agent

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