Breaking the Expectation We tend to assume that maximum tool usage means maximum advantage: use AI more, get more value. But that assumption breaks down becaus...

Introduction For years, progress in artificial intelligence was closely tied to scaling laws, where increasing model size, dataset size, and compute power led...

Action Plan Overview Artificial intelligence is reshaping cybersecurity. The same capabilities that help defenders identify vulnerabilities, automate remediati...

Accelerating Privacy‑Preserving AI Training by 81 % A new method developed by MIT researchers can accelerate a privacy‑preserving artificial‑intelligence train...

!AI Bug Slayer 🐞https://media2.dev.to/dynamic/image/width=50,height=50,fit=cover,gravity=auto,format=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploa...

!https://9to5google.com/wp-content/uploads/sites/4/2026/04/chatgpt-android-1.jpg?quality=82&strip=all&w=1600 Confident mistakes – or lies, if you will – are a c...

Most people treat study music as a playlist problem. They open a lo‑fi mix, skip a few tracks, and hope the mood is right. For developers, writers, students, an...

'APRIL 14, 2026

I was reading an article recently Long‑running Claude for scientific computinghttps://www.anthropic.com/research/long-running-Claude, which described how to set...

Training AI Reasoning Models: Challenges and a New Paradigm Training AI reasoning models demands resources that most enterprise teams do not have. Engineering...

Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant....

Bloomberg Terminal’s Growing Complexity For its famous intractability, the Bloomberg Terminal has long inspired devotion, bordering on obsession. Among traders...

Amazon launched a new AI‑powered feature on Tuesday that lets users ask questions about products and receive conversational audio responses generated in real ti...

Updates Apr 28, 2026 – 18:33 UTC We are continuing to work to resolve the issues preventing users from accessing Claude.ai, and causing elevated authentication...

Incident Timeline Resolved Posted Apr 28, 2026 – 19:15 UTC This incident has been resolved. Monitoring Posted Apr 28, 2026 – 18:59 UTC We are seeing success ra...

Recursive or looped language models have recently emerged as a new scaling axis by iteratively refining the same model computation over latent states to deepen ...

Real-world data visualization (DV) requires native environmental grounding, cross-platform evolution, and proactive intent alignment. Yet, existing benchmarks o...

Adapting reasoning models to new tasks during post-training with only output-level supervision stalls under reinforcement learning from verifiable rewards (RLVR...

How much does a user's skill with AI shape what AI actually delivers for them? This question is critical for users, AI product builders, and society at large, b...

Identity teacher forcing (ITF) enables stable training of deterministic recurrent surrogates for chaotic dynamical systems and has been highly effective for dyn...

The accelerating adoption of Large Language Models (LLMs) in software engineering (SE) has brought with it a silent crisis: unsustainable computational cost. Wh...

Distributional and neural approaches to natural language semantics have been built almost exclusively on conventional linear algebra: vectors, matrices, tensors...

Continual offline reinforcement learning (CORL) aims to learn a sequence of tasks from datasets collected over time while preserving performance on previously l...

Contact variability, sensing uncertainty, and external disturbances make grasp execution stochastic. Expected-quality objectives ignore tail outcomes and often ...

Preference-based alignment methods, most prominently Reinforcement Learning with Human Feedback (RLHF), use the judgments of human annotators to shape large lan...

Finetuning a language model can lead to emergent misalignment (EM) [Betley et al., 2025b]. Models trained on a narrow distribution of misaligned behavior genera...

Current deepfake detection models achieve state-of-the-art performance on pristine academic datasets but suffer severe spatial attention drift under real-world ...

Current pedestrian crossing signals operate on fixed timing without adjustment to pedestrian behavior, which can leave vulnerable road users (VRUs) such as the ...

Graph neural networks such as ParticleNet and transformer based networks on point clouds such as ParticleTransformer achieve state-of-the-art performance on jet...

Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representation for this...

Training language models via reinforcement learning often relies on imperfect proxy rewards, since ground truth rewards that precisely define the intended behav...

Large language models (LLMs) are increasingly used in emotionally sensitive human-AI applications, yet little is known about how emotion recognition is internal...

Existing REST API testing tools are typically evaluated using code coverage and crash-based fault metrics. However, recent LLM-based approaches increasingly gen...

Machine-generated text (MGT) detection requires identifying structurally invariant signals across generation models, rather than relying on model-specific finge...

Multimodal large language models (MLLMs) achieve ever-stronger performance on visual-language tasks. Even as traditional visual question answering benchmarks ap...

Traditional loss functions, including cross-entropy, contrastive, triplet, and su pervised contrastive losses, used for fine-tuning pre-trained language models ...

Harnesses have become a central determinant of coding-agent performance, shaping how models interact with repositories, tools, and execution environments. Yet a...

Patient simulators are gaining traction in mental health training by providing scalable exposure to complex and sensitive patient interactions. Simulating depre...

In this work, we propose Mutual Forcing, a framework for fast autoregressive audio-video generation with long-horizon audio-video synchronization. Our approach ...

Magnification shift is a major obstacle to robust histopathology classification, because models trained on one imaging scale often generalize poorly to another....

Vision-Language Models (VLMs) exhibit strong performance in instruction following and open-ended vision-language reasoning, yet they frequently generate fluent ...

Knowledge distillation (KD) is a well-known technique to effectively compress a large network (teacher) to a smaller network (student) with little sacrifice in ...

Knowledge distillation (KD) represents a vital mechanism to transfer expertise from complex teacher networks to efficient student models. However, in decentrali...

NVIDIA Nemotron 3 Nano Omni – A Unified Multimodal Model AI agents today often rely on separate models for vision, speech, and language, losing time and contex...

Google Translate adds pronunciation practice Google is celebrating Translate’s 20th birthday by launching pronunciation practice, which the company says is one...

!https://cdn-avatars.huggingface.co/v1/production/uploads/65df9200dc3292a8983e5017/Vs5FPVCH-VZBipV3qKTuy.png nvidia/C-RADIOv4-H Feature Extraction • Updated Jan...

Articulation modeling aims to infer movable parts and their motion parameters for a 3D object, enabling interactive animation, simulation, and shape editing. In...

Source Code Plagiarism Detection (SCPD) plays an important role in maintaining fairness and academic integrity in software engineering education. Code Evaluatio...