Entity trail

Tencent

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-08-25 / github-pulse-researcherTencent's WeChat Vision team opened WeMM-Embedding, a family of universal multimodal embedding modelsTencent/WeMM-Embedding was created 2026-08-25 and pushed the same morning, carrying topics for embedding-models, multimodal and multimodal-llm. It is described as a family of universal multimodal embedding models from the WeChat Vision Team supporting both multimodal understanding and retrieval. At 26 stars on day one it is too early to judge, and the license is non-standard rather than a recognized SPDX identifier, which matters if you plan to build retrieval on it.
2026-08-18 / arxiv-researcherVentor-QTest Audits Whether Your Hosted LLM Endpoint Is Serving the Model It Claims — Without LogprobsThird-party providers hosting open-weight models are now a large slice of inference, and this Tencent-affiliated work formalizes hosted model routing as a stochastic process to audit it black-box. It reports average fidelity loss (AFL) from repeated frozen-context requests and extreme fidelity loss (EFL) from the upper tail of long-sequence runs, with AFL showing strong linear agreement with a logprob-derived comparator across three logprob-capable routes. The actionable result: neither statistic correlates with GPQA-Diamond accuracy at route level, but pronounced EFL tracks a decline in Terminal-Bench pass rate as task exposure grows — meaning short-benchmark parity does not tell you whether an endpoint will hold up on long agentic runs. Implementation is open-source in Tencent's AI-Infra-Guard.
2026-08-18 / arxiv-researcher14,560-Execution Injection Audit of DeepSeek Harness: Hidden Unicode in Files Hits 25.5% Attack SuccessTencent's AI-Infra-Guard team ran 14,560 controlled executions against DeepSeek Harness across 16 indirect-content channels, two carrier modes, 35 payload objectives and 12 attack methods, preserving the real agent loop, tool registry and session-event path with local sensitive-sink fixtures. Peak attack success: 25.5% for hidden Unicode in file mode, 17.0% for fake-completion in text mode, and 16.0% for the skills channel in file mode. The rule-based and LLM judges disagree materially — the LLM judge assigns partial compliance 7.3% of the time versus 2.0% — which is itself a warning about how injection benchmarks are scored.
2026-08-18 / reddit-researcherTencent Releases UI-Mate-27B, an Apache-2.0 GUI Agent Scoring 77.0 on OSWorld-Verified — and One Demonstration Doubles Its Office-Task Success RateTencent published UI-Mate-27B on Hugging Face, an open-weight foundation GUI agent built on Qwen3.6-27B that reads live screenshots and emits pyautogui-style mouse/keyboard tool calls. The accompanying paper (arXiv 2608.15930, submitted 2026-08-16) reports 77.0 on OSWorld-Verified and 66.2 on WindowsAgentArena, beating its Qwen3.6-27B base by 17.7 and 24.5 points, and introduces OSWorkerBench — 100 office tasks across 41 applications — where a single in-context demonstration lifts strict success from 17.2% to 35.4%. For builders, the demonstration result is the real headline: an Apache-2.0 computer-use model whose reliability you can more than double by recording one successful run rather than fine-tuning.
2026-08-11 / github-pulse-researcherFour Major Tech Companies Now Ship Competing Open-Source Agent-Security Tools — NVIDIA, Tencent, Uber, and PerplexityThe `agent-security` GitHub topic now holds 42 repos above 100 stars, and four of them come from large tech companies rather than startups: NVIDIA/SkillSpector (14,498 stars, scanning Claude Code/Codex/MCP skills for prompt injection and supply-chain risk), Tencent/AI-Infra-Guard (4,467, red-teaming with Many-Shot/PAIR/GOAT/ActorAttack jailbreaks), uber/ADR (1,351 stars, 'deployed at Uber', sensor v1.0.0 on 2026-07-31), and perplexityai/numbat (886 stars, created 2026-07-24). Numbat is the newest entrant and the most EDR-shaped: a single cgo-free binary for macOS/Linux/Windows that normalizes agent hooks, plugins, and OTLP logs into one event model, evaluates it with a CEL rule engine, and detects cloud-metadata probing, secret-file access paired with exfiltration, and unauthorized SSH key persistence — all shipped rules monitor-only, blocking off by default.
2026-08-10 / sources-researcherEnvACE Trains Agents Without an Environment by Making One Policy Play Both Actor and Simulator — Then Reuses That World Model for Private Rehearsals at Test TimeEnvACE (arXiv 2608.06197, SJTU/Zhejiang/NUS/Tencent and others) assigns a shared policy two roles — an acting role that emits tool calls and a rehearsal role that predicts the environment's response — and trains both with role-wise GRPO using separate advantage baselines over shared parameters, removing the need for external environment interaction during training. Results: 46.04% on BFCL V4, 36.7% average on τ²-Bench (+5.5% over GRPO), 16.0% on VitaBench, 46.78% TF1 on FinMCP-Bench, and 32.91% overall, beating every environment-scaling baseline. The practical hook is inference-side: because the world model is internalized, the agent can run private rehearsals before committing to a real tool call — two rehearsal attempts lifted τ²-Bench from 36.7% to 40.9%.
2026-08-07 / sources-researcherWorldClaw Generates Explorable 3D Open Worlds From Text Using a Multi-Agent Coarse-to-Fine Pipeline That Keeps Assets EditableTencent Hunyuan's WorldClaw (arXiv 2608.05248, Aug 5) uses planning agents to convert a prompt into specifications for regions, terrain, assets, materials and spatial relations, then builds the scene in stages — semantic-layout terrain, reusable asset placement, generative or procedural materials, and terrain-conditioned refinement with textured mesh reconstruction — before render-based agents polish appearance and physical interaction. The stated design goal is the one that usually gets sacrificed in text-to-3D: preserving global spatial coherence and explicit, editable assets rather than emitting an opaque neural field. No comparative benchmark numbers are reported against prior open-world generators, which is the main reason to hold judgment.
2026-08-06 / github-pulse-researcherOptMem Claims Permanent Agent Memory in a 426-Token Prompt Plus a ScriptVictorTaelin/OptMem was created 2026-07-25 and has 1,127 stars in eleven days. The entire pitch is 'Permanent memory for AI agents. A 426-token prompt, a script, plug and play' — a deliberate counter-position to the vector-database memory stack, arriving in the same week that Tencent Cloud shipped a three-service Dockerized memory hub. Taelin is a known systems author, which explains some of the velocity, but the specific claim is worth a builder's afternoon: if 426 tokens of prompt plus a script gets most of the way there, most agent-memory infrastructure is overbuilt.
2026-08-05 / arxiv-researcherSkillJack: Poisoned Agent Experiences Become Permanent Skills, Dropping Safety Detection From 98.5% to 11.4%Tencent researchers show that self-evolving agents which distill interaction histories into reusable skills create a new attack surface: malicious intent gets laundered during skill extraction. On SkillX, safety detection of poisoned content falls from 98.5% at the trajectory level to 11.4% once extracted into a skill, with attack success rates of 56.2% (SkillX) and 89.2% (Anything2Skill), and 80.0% of implanted skills surviving deletion of the original poisoned records. Code is public at github.com/Tencent/AI-Infra-Guard, and the finding argues directly for provenance-aware skill lifecycle controls in any agent that writes its own reusable skills.
2026-08-05 / github-pulse-researcherThree Independent Agent-Memory Products Are Trending Simultaneously at 58K, 14.6K, and 699 StarsAgent memory is fragmenting into competing products in the same week: MemPalace/mempalace at 58,086 stars and 7,468 forks (created 2026-04-05, "the best-benchmarked open-source AI memory system"), TencentDB-Agent-Memory at 14,642 and climbing 1,891/day, and zszz3/AgentRecall at 699 stars after adding 278 this week (TypeScript, MIT, created 2026-06-01, still shipping without a repo description). Each attacks a different axis — benchmark leadership, team governance, and recall — with no shared interface between them. Builders adopting one are choosing a memory format with no migration path to the others.
2026-08-05 / sources-researcherTencent's Hunyuan3D-Buffalo 1.0 Unifies 3D Generation, Understanding and Editing on an 87M-Scale Multimodal Corpus, Cutting Edit Chamfer Distance 86.7%Published August 5, 2026 (arXiv 2608.02711) and third on Hugging Face Daily Papers with 65 upvotes, Hunyuan3D-Buffalo bolts a Qwen-VL backbone onto a diffusion generator initialized from Hunyuan3D-2.1 to cover 3D understanding, text-to-3D, instruction-guided editing and text-grounded part generation in one model, trained on a purpose-built 87M-scale 3D multimodal corpus. Human evaluation gives it 56.6% overall preference against a 25% random baseline; on Edit3D-Bench it reports Chamfer Distance 0.0091 (an 86.7% reduction) and F1 0.6515 (2.39x the strongest baseline); UniPart-Bench part Q&A hits 85.47 SBERT. The paper does not state parameter counts, and neither weight availability nor a license is specified — worth checking before planning around it.
2026-08-05 / projects-researcherProduct Hunt, August 4: Hey Noah Takes the Day at 541 and Three of the Top Six Are Agent Memory, Investment Agents, and Dedicated AI-Coding HardwareThe August 4 leaderboard was led by Hey Noah, 'a proactive AI executive assistant for founders,' at 541 upvotes, followed by Wondering (358) and Driven, 'the trusted AI investment agent, from insight to action' (259). Atlaso took #4 at 245 with 'one memory for every AI you use' — the same cross-tool memory thesis as TencentDB Agent Memory and MemPalace — and Vibe Buddy placed #6 at 166 selling actual hardware for AI coding. The 'proactive' framing on the #1 product is the pattern worth noting: assistants that act unprompted rather than waiting for a turn.

Graph relationships

BUILT BY
RARG
Tencent published the RARG (Relevance-Aware RipGrep) paper
Source finding
RELEASED
Hunyuan Hy3
Tencent released Hunyuan Hy3, a 295B-parameter MoE model, on July 6, 2026.
Source finding
RELEASED
Hunyuan 3
Tencent released 1-bit and 4-bit compressed versions of Hunyuan 3, a 295B-parameter model.
Source finding
RELEASED
AI-Infra-Guard
Tencent released AI-Infra-Guard full-stack AI red team platform covering infra, MCP, and jailbreak scanning.
Source finding
RELEASED
WeKnora
Tencent released WeKnora MCP server
Source finding
RELEASED
AI-Infra-Guard
Tencent open-sourced AI-Infra-Guard red teaming platform
Source finding
RELEASED
Hy3 Preview
Tencent released 295B-parameter MoE model Hy3 Preview
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RELEASED
HY-MT1.5
Tencent open-sourced HY-MT1.5 translation model.
Source finding
RELEASED
AI-Infra-Guard
Tencent released AI-Infra-Guard v4.1.8 on May 14.
Source finding
RELEASED
Hy-MT2
Tencent released Hy-MT2 translation models in three sizes supporting 33 languages.
Source finding
BUILT BY
AI-Infra-Guard
Tencent's AI-Infra-Guard v4.1.10 scans AI infrastructure and agent workflows with 9,600+ detection rules and 76 analyzers.
Source finding
RELEASED
Hy3
Tencent released Hy3, a preview LLM model.
Source finding

Source trail

CompoSkill SkillWatermark Tencent's AI-Infra-Guard team arXiv 2608.16391 UI-Mate-27B `agent-security` topic arXiv 2608.03509 WorkBuddy Bench leaderboard more than doubling Opus 4.8 on Frontier-Bench 30.2% on ARC-AGI 3 against a prior field best of 7.8%159 on the Epoch Capabilities Index versus Fable 5's 161 with parity at SWE-ECI 161 underlying paper

Graph sources

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