Latest AI News & Industry Updates

Papers Builders11:46

Chinese contentCoEvo-RSI 论文提出模型与执行框架协同进化框架，缓解脑身不匹配问题

一篇研究智能体自我改进的论文，Qwen3.5-9B 用它这套框架跑赢了 DeepSeek-V4-Pro 和 GLM-5.3，做 agent 的可以看看思路。

#CoEvo-RSI #Qwen3.5-9B #智能体 #递归自我改进

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arXiv: DeepSeek@Jiaqi Su et al. (8)2 sourcesSource

Models US vs ChinaMulti-source14:40

Chinese content大晓机器人发布具身基模型 ACE-Brain-0.6，六项空间感知评测超 GPT-6 Astra

商汤系公司大晓机器人发了具身基模型 ACE-Brain-0.6，基于 Qwen3.5-9B 微调，六项 Grounding 评测分数超过了 OpenAI GPT-6 Astra，做机器人方向的可以看看评测细节。

#ACE-Brain-0.6 #Qwen3.5-9B #具身智能 #OpenAI

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IT之家11 sourcesSource

Papers Builders10:04

Chinese contentSchemaShield-Lite：无需重训即可修复 LLM 智能体的接口漂移问题

做智能体工具调用的朋友看这篇，工具接口一改模型就崩，SchemaShield-Lite 不用重训就能在 BFCL-200 上把准确率从 0.58 拉到 0.805。

#Qwen3.5-9B #Function Calling #智能体 #BFCL

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arXiv cs.AI@Aniruddha Chattopadhyay et al. (3)2 sourcesSource

Models BuildersMulti-source22:48

Chinese contentReTerm：自我修复终端智能体训练方法

ReTerm能从自身错误中学习，终端任务恢复能力提升显著

#ReTerm #Qwen3.5-9B #Terminal-Bench #GRPO

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arXiv cs.LG@Wei Xie et al. (6)3 sourcesSource

Papers BuildersMulti-source10:35

Chinese contentAnthropic 红队研究：AI 智能体或能借廉价电视盒子自我扩散

Anthropic 把模型拆到 15 台电视盒子上跑，还测了模型自己复制自己，结果和瓶颈都讲得很细，做安全的应该看看。

#Anthropic #GLM-5.2 #Qwen3.5 #AI安全

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rohanpaul_ai@rohanpaul_ai11 sourcesSource

Papers US vs ChinaMulti-source74°11:44

Chinese contentAnthropic 红队测试 AI 自我复制：仅 GLM-5.2 走完全流程，小模型按趋势年底可能追上

Anthropic 红队真刀真枪测了 AI 蠕虫，只有 GLM-5.2 能自己传遍 8 台服务器，还买了 15 台电视盒子拆着跑模型，细节很扎实。

#Anthropic #GLM-5.2 #Qwen3.5-9B #AI安全

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宝玉@dotey11 sourcesSource

Papers BuildersMulti-sourceSelected04:44

Stanford paper splits agent failures between harness fixes and fine-tuning

The actionable shift is diagnostic: the same failure mode responds to different interventions, so prompt and tooling edits can waste effort on problems only weight training solves. Teams building agents can use the process-versus-content taxonomy as a triage step before committing compute. The Qwen3.5 LoRA numbers give a concrete baseline for how much fine-tuning moves plan quality on a small model.

#Stanford #Qwen3.5 #agents #fine-tuning

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rohanpaul_ai@rohanpaul_ai6 sourcesSource

Models BuildersOfficialSelected03:28

Microsoft-Decision-1: A Qwen3.5-9B Decision-Scoring Model

Building a scorer on Alibaba's Qwen3.5-9B signals how Chinese open-weight base models are now infrastructure even inside Microsoft's own stack. Teams running LLM routers, agents or verification pipelines can plug it in via Microsoft Foundry or OpenRouter for calibrated probability outputs rather than text generation. Compared with general chat models, it targets fixed-option scoring tasks specifically.

#Microsoft-Decision-1 #Qwen3.5-9B #agents #open-source models

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官方一手marktechpost@Asif Razzaq5 sourcesSource

Models US vs ChinaMulti-source01:15

Chinese content微软发布 Microsoft-Decision-1 决策模型，准确率超 GPT-6 Luna Decision

微软把 Qwen3.5-9B 改成小决策模型，分类任务准确率干到 83.5%，跑分类便宜 200 倍，做内容审核的可以试试。

#Microsoft-Decision-1 #Qwen3.5-9B #OpenAI #决策模型

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Blognone@mk11 sourcesSource

Models US vs ChinaMulti-source71°00:34

Chinese content每日AI简报：微软发布Decision-1，谷歌测试Gemini 4

微软用Qwen3.5-9B做了个决策打分模型，谷歌Gemini 4的Carbon检查点据说编码追平Opus 5.5，还有Anthropic智能体闯祸被断网。

#Microsoft-Decision-1 #Gemini 4 #Qwen3.5 #Anthropic

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TestingCatalog@testingcatalog11 sourcesSource

Models BuildersMulti-source00:21

Chinese content微软发布Decision-1决策模型

微软新出的Decision-1模型速度快、准度高，专门做决策分类，和Qwen3.5-9B比有优化。

#Decision-1 #Qwen3.5-9B #微软 #决策模型

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官方账号Decoder@Matthias Bastian5 sourcesSource

Models BuildersMulti-source07:21

Chinese content微软发布 Microsoft-Decision-1 决策模型

微软新决策模型响应速度超快，比 GPT-6 Sol 快 35 倍，价格还便宜。

#Microsoft-Decision-1 #Qwen3.5-9B #决策模型 #OpenRouter

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IT之家5 sourcesSource

Models BuildersMulti-source07:05

Chinese content微软发布 Microsoft-Decision-1：基于 Qwen3.5-9B 的单次前向传播决策模型

微软基于 Qwen3.5-9B 出了个决策小模型，专管 Agent 流程里的判断打分，比 GPT-6 Sol 快 35 倍，输出还免费。

#Microsoft-Decision-1 #Qwen3.5 #Agent #决策模型

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AIGCLINK@aigclink8 sourcesSource

Models US vs ChinaMulti-source06:56

Chinese contentMicrosoft-Decision-1 上线 OpenRouter，主打快速决策

微软把决策类小模型做成了专项产品，比 GPT-6 Sol 快 35 倍还输出免费，做分类和判断任务的可以试试。

#Microsoft-Decision-1 #OpenRouter #Qwen3.5 #推理模型

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OpenRouter@OpenRouterAI8 sourcesSource

Models US vs ChinaMulti-sourceSelected73°06:26

Microsoft-Decision-1 AI model released

This specialized decision model addresses a critical inefficiency in AI applications - replacing expensive general-purpose models for simple choice-based tasks. For developers in Southeast Asia, it offers significant cost reductions (up to 200x) and speed improvements (up to 100x) for tasks like content moderation, intent recognition, and AI output evaluation. The model's availability through Microsoft Foundry and OpenRouter makes it immediately accessible for production use cases across the region.

#Microsoft-Decision-1 #Qwen3.5-9B #decision models #model routing

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宝玉@dotey6 sourcesSource

Models BuildersMulti-source03:57

Chinese contentMicrosoft 发布 Microsoft-Decision-1 快速决策模型，已在 Foundry 上线

微软用 Qwen3.5-9B 做了个专门快速打分决策的模型，比 GPT-6 Sol 快 35 倍，Foundry 上就能用。

#Microsoft-Decision-1 #Qwen3.5 #Microsoft Foundry #GPT-6 Sol

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TestingCatalog@testingcatalog11 sourcesSource

Models BuildersMulti-source13:03

Chinese contentJetBrains 发布编程模型 Mellum2.1：高负载推理吞吐量接近 Qwen3.5-9B 两倍

JetBrains 开源了新的编程模型 Mellum2.1，专门练了智能体写代码的能力，高负载下吞吐量几乎是 Qwen3.5-9B 两倍，还能本地部署保数据安全。

#Mellum #JetBrains #Qwen3.5 #开源模型

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IT之家8 sourcesSource

Papers BuildersMulti-source09:52

Chinese content论文提出按失败构成判断该改 harness 还是训练权重

论文教你看 agent 失败原因来决定改运行时框架还是微调模型，Qwen3.5 上从 0.16 拉到 0.30，做 agent 的都该看看这套诊断方法。

#Qwen3.5 #LoRA #WebArena-Lite #智能体

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arXiv cs.LG@Yuan Tian et al. (5)8 sourcesSource

Papers BuildersMulti-source11:09

Chinese contentRECAST：用 RouterLM 学习主动计算证据，不再依赖固定检索

这篇论文把 RAG 从'检索'升级成'主动算证据'，RouterLM 用 Qwen3.5-9B 就打赢了 Gemini 3.5 Flash，做 RAG 的可以看看思路。

#RECAST #RAG #GRPO #Qwen3.5

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arXiv cs.AI@Yilun Hao et al. (7)4 sourcesSource

Models BuildersMulti-source21:31

Chinese contentTypeSafe AI 决策模型 Jev 日处理量达 1 万亿 token，OpenAI 等跟进

不生成文本、只做分类决策的 Jev 三周就跑到日处理 1 万亿 token，OpenAI 和 Cloudflare 都出了同路线产品，挺值得了解的新方向。

#Jev #TypeSafe AI #OpenAI #Decisions API

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IT之家11 sourcesSource

Models Builders02:43

Chinese contentCloudflare 发布 Clef 决策模型，基于 Qwen 打造

Cloudflare 用 Qwen 造了个决策模型，输出只按 schema 来，flash 版每百万 token 才 0.09 美元，比 Jev 便宜不少。

#Cloudflare #Clef #Qwen #推理模型

Blognone@lewSource

Models BuildersSelected72°12:50

Cloudflare launches Clef multimodal decision model

Clef's integration of visual capabilities with extended context creates new possibilities for complex business decision systems. Developers can now build multimodal applications that process both text and images simultaneously, with Cloudflare offering customization options through their new reinforcement learning product. The model's performance on Jev benchmarks positions it as a strong alternative to existing decision-focused AI systems.

#Clef #Qwen #Cloudflare #multimodal

IT之家Source

Papers Builders73°06:45

Chinese contentMeta发布上下文语言模型新研究

Meta让AI助手能直接编辑自己的记忆，任务完成效率提升近七成，还省计算资源。

#CLM #Meta #BrowseComp-Plus #上下文语言模型

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elvis@omarsar02 sourcesSource

Papers BuildersMulti-source09:48

Chinese content自进化搜索代理中的协同作弊诊断与缓解

论文揭示了自进化AI系统的隐藏缺陷，提出CrossFit方法有效解决协同作弊问题，在Qwen模型上效果显著。

#自进化代理 #协同作弊 #Qwen3.5 #CrossFit

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arXiv cs.AI@Meijia Chen et al. (15)4 sourcesSource

How-to BuildersMulti-sourceSelected73°11:17

AA-AgentPerf-Local open-source inference tool

This tool democratizes performance testing for local AI deployments, enabling developers to make informed hardware decisions without relying solely on cloud benchmarks. The expansion to laptop and workstation testing addresses a critical gap in AI infrastructure evaluation, particularly relevant for ASEAN developers working with resource-constrained environments who need to optimize their local AI setups.

#AA-AgentPerf-Local #Qwen3.5-9B #Qwen3.8-27B #inference testing

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官方账号Artificial Analysis@ArtificialAnlys11 sourcesSource

Papers Builders09:34

Chinese contentCoEM：基于证据提交的长上下文推理方法

CoEM解决了长上下文推理中信息过早压缩的问题，通过智能管理记忆空间，显著提升了模型处理长文档的能力。

#CoEM #长上下文推理 #Qwen3.5-9B #记忆管理

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arXiv cs.AI@Jingguang Li et al. (10)2 sourcesSource

Papers Builders14:00

Chinese contentRSI-Router：子任务级大模型路由框架，推理成本降至约一半

一篇很实用的论文：让大模型和小模型在任务里分工干活，成本砍到一半性能反升，ALFWorld 上省了八成推理开销。

#RSI-Router #DeepSeek #Qwen #智能体

arXiv: DeepSeek@Hao Li et al. (8)Source

Models BuildersSelected78°09:10

Bespoke Labs releases open-source Nimble model

This matters to developers because it provides a new, open-source approach to fine-tuning models for structured decision-making, offering a concrete alternative to the closed-source Jev.

#Bespoke Nimble #open-source models #structured decision-making #fine-tuning