AI Dataset2026
Behavior-preserving dataset of GLM 5.2 coding and debugging agent trajectories for supervised fine-tuning and analysis; contains 1,821 cumulative next-step rows from 207 verified trajectories with multi-turn tool use, build-test-fix loops, and runtime-normalized traces.
AI Dataset2026
Provides 50 ARC‑AGI‑3 gameplay trajectories (GPT‑5.6 Sol and Claude Opus/Fable) plus a dependency‑free scorer and event logs; includes sanitized session data, snapshots, and utilities to recompute RHAE scores for reproducible agent evaluation and cross-model comparison.
AI Agent Papers2026
Turns fragile, implicit search progress into explicit, persistent, shared state for multi-agent information seeking — externalizes progress as Frontier Task, Evidence Graph, Coverage Map and Failure Memory, and uses pipeline-parallel scheduling plus a middleware harness to avoid repeated failed searches and improve utilization and throughput.
AI Agent Papers2026
Guides an LLM agent to build persistent, editable DAG-based data pipelines via typed, incremental mutations instead of free-form scripts. Combines DataFlow-Skills, a Model Context Protocol exposing live operator registry and pipeline state, and a synchronized Web UI; achieves 93.3% end-to-end pass rate on a 12-task benchmark while cutting cost and latency versus script baselines.
AI Dataset2026
Provides verified, model-attested end-to-end agent coding and debugging trajectories (JSONL). Each whole-session trace was produced by moonshotai/kimi-k3 on the pi/openrouter runtime, passed acceptance tests and independent model screening — useful for SFT, distillation, and analyzing tool-use behavior.
AI Agent Papers2026
Models long-horizon interactive literary simulation where characters and world co-evolve; introduces an open‑schema framework with a Character Agent and an LLM-based World Model, plus seven trainable tasks and a dataset from 57 books for benchmarking persistent narrative state.
AI Dataset2026
Provides newline-delimited JSON agent session traces (5 files) generated with Teich for moonshotai/kimi-k3, including recovered and embedded tool-schema snapshots so traces remain training-ready even when tools weren't invoked; includes guidance for Teich data preparation and conversion.
AI Agent Papers2026
Prunes tool-output lines inside a coding LLM agent by turning the agent's own internal representations into per-line keep-or-prune labels. Implements a small classification head plus a length-aware embedding, saving up to 39% of tokens across benchmarks while preserving task quality.
AI Model2026
1B-parameter text-generation model tuned for conversational and agentic workflows with a focus on security and vulnerability-detection; suited for low-cost or on-prem/edge deployments and terminal-agent integrations.
AI Model2026
Compact 3B-scale agentic LLM for multi-step tool use and reasoning, using a Looped Transformer to increase capacity without adding parameters; built for local deployment with configurable "thinking" modes and benchmark gains vs larger open models.
A PyTorch-native training framework for agentic reinforcement learning research that keeps researcher-facing code compact and editable. Uses an asynchronous loop to train multimodal and mixture-of-experts policies while never training on tokens the agent didn't generate; matches Megatron-style stacks under a comparable protocol and ships recipes and containers on GitHub.
AI Model2026
An open-weight LLM checkpoint post-trained for agentic deep search: Qwen-compatible reasoning and tool-call formats optimized for web browsing, multi-source evidence aggregation, long-horizon planning and recovery from failed interactions; typically paired with the AxisAgentic harness.