AI Dataset2026
Provides a token-level benchmark for Russian PII detection and NER, with 2,841 sentences and 5,614 annotated spans across 21 fine-grained entity types in BIO format. Mixes sanitized production-log examples, synthetic document templates, and hard negatives to evaluate guardrails and anonymization pipelines.
AI Dataset2026
Benchmark for evaluating multimodal LLM safety in Korean cultural contexts — includes KSAFE-MM-G which localizes global safety queries into Korean scenarios and KSAFE-MM-C which targets culture-specific visual-textual vulnerabilities. Provides curated image–text pairs and jailbreak-style prompts to reveal both unsafe behaviors and over-refusal.
AI Agent2026
Orchestrates, composes, and governs multiple AI agents (Claude Code, Codex, Cursor, Pi, and custom agents) via a meta-harness that enforces policy-based sandboxing, spend caps, and live collaborative sessions. Agent behavior is declared in YAML and can run locally or in managed cloud sandboxes.
AI Agent2026
Turns a coding agent into a multi-phase security auditor that orchestrates isolated sub-agents for reconnaissance, coverage-led hunting, adversarial validation, structured JSON findings, and independent verification. Requires Node.js and a sandboxed runtime.
AI Model2026
Provides GGUF-quantized weights and runtime assets for running the Qwythos-9B reasoning LLM locally via llama.cpp and compatible runtimes. Key features include 1,048,576-token YaRN long-context, native function-calling, multimodal image input (requires mmproj), and multiple quantization/MTP variants tuned for different size/quality tradeoffs.
AI Model2026
A 9B reasoning LLM fine-tuned from Qwen3.5 that ships with a 1,048,576-token context, native function-calling and tool-use, and notable benchmark gains (+34 MMLU, +30 gsm8k-strict).
AI Agent Papers2026
Matches detection paradigms to four stratified attack-surface layers of AI agents — infrastructure, protocol/tool, agent behavior, and model — and presents AI-Infra-Guard: an open-source red-teaming framework with rule-based infra scanning, LLM-driven audits of MCP servers and skill packages, and a jailbreak/attack-operator harness.
AI Infra2026
Indexes mixed-format folders locally into a zero-config, Elasticsearch-compatible search engine offering keyword, semantic, vector and hybrid retrieval. Embeds on ingest, provides per-agent namespaced memory and AST-aware code indexing in a single static binary with no external embedding key.
AI Model2026
27B multimodal reasoning model built on Qwen3.5-27B that preserves the base model's native multi-token-prediction head, full vision tower, and a 1,048,576-token YaRN context window. Designed for agentic tool use, long-context reasoning, and research deployments; released under Apache-2.0.
AI Agent2026
Scans repositories, selected paths, or Git changes to find and investigate vulnerabilities. It can also validate findings, generate patches, and check whether fixes work.
AI Dataset2026
Provides live Codex-CLI agent run traces from GPT-5.6 Sol capturing coding, debugging, security reviews, and harness/seed workflows in cumulative next-action prefixes — suitable for supervised fine-tuning and analysis of tool-using coding agents.
Embodied AI2026
Analyzes adversarial weaknesses of World-Action Models (WAMs) via BadWAM, a framework that crafts visual perturbations to decouple a model’s imagined future from its executed actions. Introduces two attack modes—action-only (disruptive) and imagination-preserving (stealthy)—and shows large drops in closed-loop task success (e.g., 96.5%→43.1%).