AI Intelligence Archive
浏览 AIQB 已保存的 6366 stories AI intelligenceArticles,覆盖Models、Products、Industry、Research、教程与观点方法六大分类。
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TutorialsOrdinary
Epistemological corrosion created by machine induced semantic replication entropy
The headline is a extract of a skeet from a gamedev/designer/dev person of Bluesky: Osaka Skilled...
Source: DEV Community
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Preptember is here!! Plan a Fest for your local community.
September marks the official start of Preptember, a month dedicated to organizers planning local...
Source: DEV Community
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How to Leverage AI in Web Development Frameworks in 2026
Learn exactly how to leverage AI in web development frameworks in 2026. Real stats, real tools, prices, and actionable workflow upgrades. No fluff—just results.
Source: DEV Community
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How to Integrate AI Coding Tools in Agile (2026 Data & Tactics)
See how to integrate AI coding tools in Agile development: 2026 stats, tool costs, pitfalls, and actionable playbooks. AI team velocity, ceremonies, and quality metrics.
Source: DEV Community
TutorialsOrdinary
I Built an Agent to Fix Bad Tests. I Found Eight Bugs in My Own Ruler.
Here is a Python function and a test for it. def withdraw(balance, amount): if amount <=...
Source: DEV Community
ResearchOrdinary
Beyond Scores: Understanding LLM-as-a-Judge Mechanisms in Summarization Evaluation
LLM-based evaluators of natural language generation (NLG) quality are widely deployed as scoring tools and as automated training signals, yet the internal procedure by which they assign a rating remains poorly understood. We investigate th…
Source: arXiv · Llama / Mistral
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Efficient SWE Agent Benchmarking via Trajectory-Aware Evaluation
Evaluating software engineering agents on realistic benchmarks is costly, since each task may require multi-step code exploration, modification, and test execution. Existing efficient evaluation methods select representative subsets to est…
Source: arXiv
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Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation
The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repository context. Since real-world repositories often exceed the input length limits of LLMs…
Source: arXiv
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CordisBench: Can Language Models Reason About Component Lifecycles in Dynamic Agent Harnesses?
Dynamic agent harnesses let language models change the software that shapes their own execution. This flexibility brings a new reasoning burden: a local plugin change can propagate through dependencies and cleanup. We introduce CordisBench…
Source: arXiv · GPT
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The Rise of Verbal Reinforcement Learning
Natural language is emerging as a primary feedback channel for improving language agents, capable of conveying intent, preferences, and causal structure in forms interpretable by both humans and modern language models. We call this paradig…
Source: arXiv
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Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation
Real-world robotic assembly at sub-millimeter tolerances demands spatial precision, compliant interaction, and robustness to contact failures. We present Facet-0, a robotic foundation model that predicts and values the contact consequences…
Source: arXiv
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Mechanism Design for Alignment and Control
We develop a framework for mechanism design with AI agents whose alignment (preferences) and capabilities (feasible actions and information) are unknown. We want such agents to act on our behalf so mechanisms must incentivize both honesty …
Source: arXiv
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StudentSim: Training LLM-based Student Simulators
AI tutors are most useful when they adapt to each student's strengths, weaknesses, and preferred guidance, but evidence about which guidance works for which student is sparse, slow, and costly to collect from real learners. Student simulat…
Source: arXiv · GPT
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Designing Proactive Thought Partners for Writing
Writing involves diverse cognitive activities, from ideation to revision, and writers' needs vary across individuals and moments. Proactive AI promises to provide the right support at the right time, yet existing proactive tools largely fo…
Source: arXiv
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The Structure of Quantization Damage in LLMs: Why the Next Bit Should Be Spent Globally
Post-training quantization (PTQ) is widely used to reduce the cost of serving large language models (LLMs), but its accuracy cost is uneven and is often tuned per model. We study where quantization damage occurs and how to allocate a small…
Source: arXiv · Qwen
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I Built an AI That Rewrites Its Own Prompts — Its Safety Gate Rejected Every Single Edit
AgentSelfEdit is an open-source sidecar that rewrites its own system prompt from execution feedback....
Source: DEV Community
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The Agent Knew It Was Wrong. The System Let It Ship
In 660 of 800 autonomous research runs, the agent found a critical flaw and delivered the result anyway. Self-review is not a control unless it can block the effect.
Source: DEV Community
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Closing Cost-Quality Gap in Document VLMs: Difficulty-Aware Data Curation and Quality-Adjusted Deployment Economics
Extracting structured fields from hundreds of millions of documents annually remains costly in regulated industries: bespoke OCR cascades cover only a fraction of workflows, privacy rules preclude external models, and existing open-source …
Source: arXiv
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Scaling Near-Optimal SFT-RL Annotation Budget Allocation from Small to Large LLMs
How to divide a fixed annotation budget between supervised fine-tuning (SFT) and reinforcement learning (RL) during LLM post-training remains an open problem. Existing work characterizes only broad trends (e.g., SFT dominates in low-data r…
Source: arXiv
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From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix
Data-residency constraints force enterprises to self-host LLMs, but continuous adoption of newer models without decommissioning their predecessors expands the serving fleet, fragmenting a finite GPU pool. We consolidate traffic from over 2…
Source: arXiv
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Selective Agent Guidance via Entropy: Learning Autonomous Policies from Imperfect VLM Teachers
Vision-Language Models (VLMs) provide useful priors for interactive decision-making, but using them directly as policies is expensive and brittle: they must be queried at every step, do not improve from environment interaction, and can rep…
Source: arXiv
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From Confusion to Clarity: Confusion-Aware Retrieval and Knowledge Injection for Text Classification
Large language models (LLMs) struggle to classify text into taxonomies with many semantically similar labels, as the distinctions are domain-specific and not captured by pre-training. To handle large label spaces, a common approach retriev…
Source: arXiv
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A systematic Approach to constructing a Chance-and-Risk Matrix for Semiconductor Supply Chains
Semiconductor supply chains face escalating risks from geopolitical tensions, geographic concentration, and rapid technological shifts, yet no scalable system continuously extracts, structures, and prioritizes risk intelligence from public…
Source: arXiv
ResearchOrdinary
H3-World: Turning Language Understanding into World Control
We present H3-World, an efficient framework that turns the 33B MiniMax-H3 video generator into an interactive world model. Our key finding is that, as large video generators become more capable, language is emerging as a natural interface …
Source: arXiv
ResearchOrdinary
Gradient-Update Mismatch: Rethinking Conflict-Free Training of Physics-Informed Neural Networks
Training Physics-Informed Neural Networks (PINNs) requires jointly optimizing physics residual and initial/boundary condition loss terms, which often induce conflicting gradients. Gradient surgery methods mitigate this issue by constructin…
Source: arXiv
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Retrieved but not ranked: surface-form bias in structural retrieval, from mathematics to agent trajectories
We evaluate embedding retrieval where surface form and meaning are pulled apart on purpose: retrieving items that share underlying structure but not wording, in two unrelated domains under one protocol, competition mathematics (MathNet-Ret…
Source: arXiv
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BS: Take the Hint - Interactive Multitracer PET/CT Lesion Segmentation with a Scribble-Conditioned ResEnc U-Net
Automated lesion segmentation in whole-body PET/CT is complicated by the variety of physiological tracer uptake patterns and by the differing appearance of lesions across tracers. The autoPET/CT V challenge addresses this by making segment…
Source: arXiv
TutorialsOrdinary
Render MCP Apps in your own host in 5 minutes
In January, MCP Apps (SEP-1865) became the first official extension to the Model Context Protocol,...
Source: DEV Community
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On-Policy Distillation Works Better Without the Teacher
A new Purdue paper analyzed teacher supervision in on-policy distillation. The teacher scores are mostly noise, and a fixed negative penalty beats a full teacher model on AIME24.
Source: DEV Community
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Designing a BYOK AI Architecture for a Commercial Framer Template
I Built an AI-Enabled Framer Template Without Owning the Buyer’s AI Most AI-enabled websites hide an...
Source: DEV Community
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How to Design AI Evaluations You Can Actually Trust
As part of my work at Google, we are publishing a suite of Agent Skills for Google products and...
Source: DEV Community
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Building a Zero-Download Digital Disposable Camera \
Collecting candid photos and videos from guests at weddings, parties, and offsites has always been a...
Source: DEV Community
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I Gave Claude Code a Brain. Then I Measured What It Costs to Ask for One.
At the end of part 2 I promised a clean competitor comparison: more than one memory system, the same...
Source: DEV Community · Claude
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The Brave Wanderer: I made Claude play a Pokémon it never read a guide for
The Brave Wanderer: I made Claude play a Pokémon it never read a guide for Full timeline...
Source: DEV Community · Claude
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I raced six models against each other on DigitalOcean Inference. The cheapest one won.
Every time I put a model behind an endpoint I make the same lazy decision. I pick whatever I used...
Source: DEV Community
TutorialsOrdinary
Kubernetes is HariKube's query language, control protocol, and application interface for managing data streams
Building production-grade microservices has meant wrestling with legacy anti-patterns, dealing with...
Source: DEV Community
TutorialsOrdinary
Streamline Publishing with a Claude Code Skill
A Claude Code skill that turns one markdown file into dev.to, AWS Builder Center, Medium and LinkedIn versions, checks them before they ship, and posts the ones with an API — plus the debugging tools for when a destination mangles somethin…
Source: DEV Community · Claude
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Divide and Let the LLM Do the Rest: From Personal Experience to Architecture
Where This Started A few years ago, I started thinking about a simple question: How far...
Source: DEV Community
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What happens to technical debt when AI makes code cheap?
Dear past Jenna, I know you're used to dealing with large, complex, legacy codebases riddled with...
Source: DEV Community
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7 production checks I run after an AI website builder ships
Seven practical checks for editability, lead delivery, measurement, recovery, portability and independent handover after an AI-built site ships.
Source: DEV Community