2026-08-12

DistilVDR: A Compact End-to-End Visual Document Retriever via Dual-Student Distillation

👍 2

08/11 08:00

Visual document retrieval (VDR) is dominated by multi-billion-parameter models that are slow to index at full corpus scale and expensive to serve. Prior compression routes either train a smaller multi-vector encoder from scratch or distil only the query side; neither yields a compact single-vector r

Reference-Free Post-Training of Open Large Language Models for Multilingual Machine Translation

👍 3

08/11 08:00

We study reference-free post-training for multilingual machine translation with open large language models. Starting from the supervised-finetuned MiLMMT-46-v0.1 models, we apply Group Relative Policy Optimization (GRPO) with a reward that averages two reference-free quality estimation models and is

ComBodied Agents: a New Paradigm of Human-Centric Agentic AI

👍 47

08/11 08:00

After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication. Yet neither explains whether the person forgot, is confused, has side effects, or deliberately refused, nor what support is appropriate. This reveals a structural

SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure

👍 4

08/11 08:00

Self-evolving agents accumulate reusable skills by appending successful procedures and failure fixes. Over time, the same requirement is often restated in several branches, examples, and warnings, while common action sequences are copied rather than reused. The resulting skill becomes expensive to i

DSAgentBench: Can Agents Automate End-to-End Data-Science Workflows in Real Computer Environments?

👍 1

08/11 08:00

Real-world data science involves long-horizon workflows that span data wrangling, exploration, modeling, visualization, and validation, and require coordinated use of tools such as notebooks, IDEs, terminals, browsers, and databases within real operating environments. Yet existing benchmarks lack re

SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information

👍 5

08/11 08:00

Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across multiple applications (apps) to complete user instructions. However, due to the lack of dedicated benchmarks, their capabilities remain poorly unders

VibeLifeBench: Can Your Life Agent Be Proactive and Persistent in a Living World?

👍 5

08/11 08:00

Large language model (LLM) agents are increasingly deployed as personal assistants. Existing evaluations, however, mostly use short, self-contained requests in static environments. Everyday life assistance is different. A task runs for weeks rather than minutes. The world keeps changing while the ag

Decoding-Level Taboo: A Diagnostic Stress Test for LLM Robustness

👍 5

08/10 08:00

Large language model evaluations typically focus on performance under nominal conditions, creating an illusion of capability where models comfortably walk a narrow, highly optimized generation corridor. In real-world deployments, however, complex system prompts, safety guardrails, and structural con

Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

👍 56

08/10 08:00

Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, such as fixed tasks and feedback. This survey focuses on co-evolution in agentic systems, a multi-component form of self-evolution in which multiple

BDH-CQ: In-Context Learning with Recurrent Latent Reasoning

👍 285

08/10 08:00

We introduce BDH-CQ, a reasoning model that combines in-context learning with recurrent latent reasoning. Inputs presented at inference time continuously update the model's recurrent memory; the model then solves a query through iterative computation in a high-dimensional latent space, without verba

CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems

👍 5

08/10 08:00

The development of embodied Intelligent Virtual Agents (IVAs) that have cognitive capabilities in real-time interactive virtual environments remains a challenge, even with today's advancements in technology. Existing architectures are often focused on either the implementation of low-level reactive

Stealing Reasoning Traces from Proprietary LLM APIs

👍 65

08/10 08:00

Leading large language model providers now conceal their models' step-by-step reasoning, or chain-of-thought, to protect intellectual property and limit information leakage. Rather than storing these traces server-side, providers return them to the client as blocks of encrypted text, which the clien

Not Worth Another Token: Marginal Value Estimation for Efficient Deep Research Agents

👍 3

08/09 08:00

Long-horizon research agents solve open-ended tasks through iterative retrieval, aggregation, and synthesis, but context grows rapidly while the marginal value of additional evidence often declines. This leads to unnecessary token cost, higher latency, and noisier inputs for final report generation.

VectraYX-Vision-1B: A Sub-2B Spanish/LATAM Cybersecurity Vision-Language Model with Structured Visual Reasoning and Native Tool Use

👍 5

08/09 08:00

We present VectraYX-Vision-1B, a sub-2B vision-language model (VLM) for Spanish/LATAM cybersecurity imagery, coupling a frozen SigLIP-so400m encoder to a 1.04B Spanish/LATAM security decoder via an MLP. To our knowledge, it is the first sub-2B VLM specialized for cyber UI (IDA, Ghidra, Wireshark, Nm

On-Policy Self-Distillation without Any Supervision

👍 159

08/09 08:00

On-policy (Self-)Distillation (OPD / OPSD) has shown strong potential for post-training large language models (LLMs). However, existing methods still rely heavily on external supervision, including ground-truth signals, environmental feedback, or guidance from larger models, and therefore fall short

Business Arena: Benchmarking LLM Agents in a Realistic Marketplace

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08/09 08:00

Running a business is a challenging form of intelligent work. Operators must infer opportunities from partial signals, commit capital under uncertainty, adapt to delayed outcomes in a changing market, and satisfy regulatory obligations before trading legally. Frontier LLM agents can increasingly com

Gaming Without an Attacker: Benchmark Fingerprinting in LLM-Driven Search Under Selection Pressure

👍 6

08/09 08:00

Benchmarks for systems that are optimized against the evaluation signal measure something different from what they claim. We document this concretely in two GPU-kernel-optimization suites with held-out generalization gates: Metal-Sci (10 scientific-compute tasks) and Metal-ZK (12 zero-knowledge/cryp

SymDiag: Explainable Diagnosis for LLM Reasoning via Neuro-Symbolic Verification

👍 5

08/09 08:00

Large language models (LLMs) increasingly serve as data-driven reasoners, yet their chains-of-thought (CoT) can be unfaithful even when final answers are correct. Most existing ``verification'' signals are not diagnostic: answer matching observes only the outcome, LLM-as-judge provides subjective an

TSDS-Toolbox: A Toolbox for Measuring Time-Series Dataset Similarity

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08/08 08:00

The rapid advancement of artificial intelligence (AI) has significantly accelerated research in time-series analysis, particularly in forecasting, classification, and generation tasks. Recent models, especially foundation models, benefit from time-series dataset similarity due to its significant rol

A Hybrid Nested Harness for Decoupling Structure and Parameters in LLM-Driven Optimization

👍 6

08/08 08:00

In evolutionary algorithms powered by language models, the LLM acts as a single operator that simultaneously updates structural components (like control flow) and continuous parameters. While LLMs can be good at the first, they are not efficient at the second, wasting tokens taking discrete jumps in

Ego-OSCAR: Egocentric Open source Stereo CAptuRe System

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08/08 08:00

We present Ego-OSCAR, an open-hardware, low-cost, head-mounted stereo-inertial capture device for egocentric data collection in the wild. EgoOSCAR pairs a hardware-synchronized global-shutter stereo camera with a 6- axis IMU, an embedded Linux SBC for on-device video encoding, and a realtime microco

iFAN: Inference-Aware Learning for Plain Mask Transformers

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08/07 08:00

Query-based mask transformers assemble segmentation outputs through pixel-wise competition among query predictions of the final layer, yet this inference process is not explicitly optimized during training. We identify two key mismatches: the query with the highest probability-mask score does not ne

Mendel Gödel Machine: Recursive Self-Improving Coding Agents via Comparative Evolution

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08/07 08:00

Self-improving coding agents that iteratively rewrite their own source code have demonstrated impressive performance on coding tasks. However, existing solutions generally derive self-modification from a single failure trajectory at a time, overlooking rich comparative signals available in the agent

Beyond Starry Night: Shortcut-Aware Control-State Planning for Artist-Grounded Text to Image Generation

👍 5

08/07 08:00

Artist-grounded image generation requires more than appending an artist name to a prompt. Image models often respond to artist names through canonical shortcuts, such as recurring motifs, generic palettes, or overrepresented period signatures, rather than preserving the user's intended scene. We int

MirrorWorld: Taming Video Diffusion Models for Mirror Reflection Generation

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08/07 08:00

Recent advances in video diffusion models (VDMs) have enabled high-fidelity video synthesis. However, generating mirror reflections remains challenging because the content within a mirror must remain consistent with the surrounding scene. Existing VDMs are not specifically designed to model scene-to

The Next Screenshot Knows: Gated Hindsight Distillation for Mobile GUI Agents

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08/06 08:00

GUI agents are commonly trained offline from successful interaction trajectories. Standard training decomposes each trajectory into prefix-action pairs: the agent predicts an action from the current screen and interaction history, while the subsequent observation is discarded. This removes the ratio

JigShape: Evaluating Visual-Geometric Reasoning in VLMs through Jigsaw Puzzles

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08/04 08:00

Jigsaw puzzle solving requires jointly reasoning about visual content and geometric constraints, yet existing benchmarks use rectangular cuts that create ambiguous ground truth in texture-repeated regions. We introduce \ours{}, a benchmark with tab-and-blank interlocking pieces where geometric const

Omega-S: A Functional Resilience Index for LLM Fine-Tuning

👍 5

08/04 08:00

Fine-tuning a large language model on new data degrades what it previously learned. We present Omega-S, a drop-in penalty computed from the weight matrix alone: it needs no previous-task data, no Fisher matrix and no stored copy of the old weights. It is three lines in an existing training loop and

WeClawArena: An Auditable Sandbox and Benchmark for Cross-User Agents Collaboration and Security in Human-Centered Agent Networks

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08/04 08:00

Recent advances in persistent personal-agent frameworks are making human-centered agent networks realistic deployment targets: each user can be served by an AI agent that acts on the user's behalf, maintains state, and communicates with other agents through social and task relations. In these networ

MMOOC: A Comprehensive Benchmark for Out-of-Context Evaluation in Multimodal Large Language Models

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08/01 08:00

Multimodal Large Language Models (MLLMs) have achieved strong performance on a wide range of vision-language tasks, but often fail under imperfect or shifted contexts. A reliable MLLM should refuse truly out-of-context (OOC) questions with subject-level context shifts while still answering shifted i

How to Build a Shared AI Harness for Your Team

@VibeMarketer_ · 30.1K 粉丝 · 107.1K 阅 · 528 赞 · 29 转

08/10 21:36

I am going to show you how to turn the models, agents, skills, and automations living across your team's tools and workflows into one coordinated system. What most teams have today looks very

中文介绍 分享如何构建团队共享AI系统，将分散的工具和工作流中的模型、代理、技能和自动化整合为一个协调系统。

NVIDIA Nemotron 3.5 Lightning and NeMo Switchyard Deliver Faster, Smarter, More Efficient Agentic AI

@nvidia · 2.6M 粉丝 · 59.5K 阅 · 548 赞 · 66 转

08/11 21:41

The new lightweight open model and routing library delivers greater control over AI, data and workflows across edge devices, PCs, workstations, data centers and the cloud. Source: NVIDIA Blog By Kari

中文介绍 介绍NVIDIA Nemotron 3.5 Lightning和NeMo Switchyard，提供更智能、高效的边缘设备、PC、工作站、数据中心和云端的AI、数据和流程控制。

7 rules for self-improving agent loops every AI engineer should know

@GoogleCloudTech · 1.3M 粉丝 · 46.8K 阅 · 505 赞 · 63 转

08/11 01:57

By @Saboo_Shubham_ and @secchi_elia When coding agents write the code, defining what's good is the real engineering job. Coding agents can now build and improve other agents. Write the instructions,

中文介绍 分享7条AI工程师应知的自我改进代理循环规则，强调编写代码时定义“好”的标准是真正的工程任务。

Intro to Grok Bot

@mattyp · 44.5K 粉丝 · 33.5K 阅 · 651 赞 · 48 转

08/12 02:59

I’m always chasing better tools. Notes apps, workflows, optimizations, and now, personal agents. It’s an easy trap to fall into - always building the “custom” thing and sacrificing the work as a

中文介绍 介绍Grok Bot，强调寻找更好工具的重要性，并讨论避免过度定制化而牺牲工作效率的问题。

[AINews] How to steal a Reasoning Trace

Latent Space · 08/12 15:11

Speculative Decoding by any other name would distil as sweet

中文介绍 Latent Space探讨如何窃取推理轨迹，提出假设性解码技术。

🔬The BioAI Phase Shift - Matthew McPartlon & Neil Patil, Chai Discovery

Latent Space · 08/12 05:03

Pharma is suddenly paying for Bio × AI tools, and Chai is leading the pack with four deals closed this summer. Cofounder Matt McPartlon and Product leader Neil Patil explain why.

中文介绍 Chai Discovery在生物AI领域取得突破，今年夏天已达成四笔交易。

Thinking of ACE? We Can Do It with Fewer Tokens

Hugging Face Blog · 08/11 21:37

中文介绍 Hugging Face Blog介绍ACE模型，使用更少标记实现。

Testing ads in ChatGPT

OpenAI News · 08/11 18:00

OpenAI begins testing ads in ChatGPT to support free access, with clear labeling, answer independence, strong privacy protections, and user control.

中文介绍 OpenAI开始在ChatGPT测试广告，支持免费访问，保障用户隐私。

Daybreak models are now available on AWS

OpenAI News · 08/11 18:00

OpenAI and AWS are making Daybreak cybersecurity capabilities available through Amazon Bedrock to support enterprise security workflows.

中文介绍 OpenAI与AWS合作，将Daybreak网络安全能力通过Amazon Bedrock提供。

[AINews] Muse Glimmer and Spark: Open Weights return Personal Superintelligence promise

Latent Space · 08/11 13:16

a small win for american open models - Glimmer runs on a fits on a single RTX 3090!

中文介绍 美国开放模型Glimmer在单RTX 3090上运行，展示个人超级智能潜力。

Muse Glimmer ✨, OpenAI Cyber 🛡️, Claude vs Riemann Hypothesis 🧠

TLDR AI · 08/11 08:00

中文介绍 TLDR AI讨论Muse Glimmer、OpenAI网络安全、Claude与黎曼猜想。

AI professors are negotiating the new realities of academic research

MIT Tech Review AI · 08/11 04:00

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Last week, I headed 30 miles south of San Francisco to a hotel in Mountain View, California, to join some of the most accomplished, and some of the most promising

中文介绍 MIT Tech Review AI报道AI教授探讨学术研究的新现实。

What building an AI-native finance function taught me

OpenAI News · 08/11 01:00

OpenAI CFO Sarah Friar shares five lessons for building an AI-native finance function, from automated forecasting to stronger controls and AI ROI.

中文介绍 OpenAI首席财务官分享建立AI原生财务功能的五项经验。

Build Low-Latency Multilingual Voice Agents: Open Weights & Full Deployment Control with NVIDIA Magpie TTS

Hugging Face Blog · 08/11 00:25

中文介绍 Hugging Face Blog介绍使用NVIDIA Magpie TTS构建低延迟多语言语音代理。

OpenAI’s letter to Governor Abbott on responsible AI infrastructure in Texas

OpenAI News · 08/10 22:00

OpenAI sent Governor Greg Abbott a letter outlining its commitment to responsible AI infrastructure in Texas. The letter supports reliable, transparent growth that benefits Texans.

中文介绍 OpenAI致德克萨斯州州长阿博特信函，承诺在德克萨斯州建设负责任的AI基础设施。

Model ML completes finance work more efficiently with GPT-5.6 Sol

OpenAI News · 08/10 20:00

Model ML uses GPT-5.6 Sol to carry finance work from research and analysis through editable, traceable PowerPoint decks and Excel workbooks.

中文介绍 Model ML利用GPT-5.6 Sol提高金融工作效率。

Making Knowledge Distillation Cheap Enough to Run at Scale

Hugging Face Blog · 08/10 18:05

中文介绍 Hugging Face Blog探讨高效知识蒸馏，使其在规模上可行。

Expanding Daybreak as the Cyber Defense Window Narrows

OpenAI News · 08/10 18:00

Meet GPT-5.6-Cyber, OpenAI’s cybersecurity-specific model available through Daybreak Red for authorized vulnerability research, exploit validation, and security testing.

中文介绍 OpenAI扩大Daybreak模型，以应对网络安全窗口缩窄。

Putting frontier cyber models in more trusted hands

OpenAI News · 08/10 18:00

Approved Daybreak partners can use OpenAI’s frontier cyber models to deliver authorized, governed cybersecurity services to customers.

中文介绍 OpenAI将前沿网络安全模型授权给Daybreak合作伙伴，提供受控的网络安全服务。