Large language models frequently exhibit suboptimal performance on low resource languages, primarily due to inefficient subword segmentation and systemic traini...
Language models achieve impressive performance on a variety of knowledge, language, and reasoning tasks due to the scale and diversity of pretraining data avail...
Binary vulnerability analysis is increasingly performed by LLM-based agents in an iterative, multi-pass manner, with the model as the core decision-maker. Howev...
on LinkedIn a few days ago saying that a lot of the top engineers are now just using AI to code. It reached thousands and got quite a few heated opinions. The s...
FL has emerged as a transformative paradigm for ITS, notably camera-based Road Condition Classification (RCC). However, by enabling collaboration, FL-based RCC ...
!Sora splash screenhttps://www.androidauthority.com/wp-content/uploads/2025/11/sora-splash-screen-logo-app-scaled.jpg TL;DR - OpenAI introduced its Sora app for...
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, we talked in detail about what Prompt Cachinghttps://towardsdatascience.com/why-care-about-promp-caching-in-llms/ is in LLMs and how it can save you a lot of...
The Biggest Lie in Machine Learning If you’ve been around ML for even a bit, you’ve seen this pattern: - train model - get 90%+ accuracy - post screenshot - fe...
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LLM-powered agents are emerging as a dominant paradigm for autonomous task solving. Unlike standard inference workloads, agents operate in a strictly serial 'LL...
learns machine learning usually starts with linear regression, not just because it’s simple, but because it introduces us to the key concepts that we use in neu...
It’s a double feature on GeForce NOW Thursday. This week, GeForce NOWhttps://www.nvidia.com/en-us/geforce-now/ offers smoother sights in virtual reality VR and...
Overview Adobe is launching customizable AI image generators that can mimic specific artistic styles and character designs. The Firefly Custom Models are avail...
— collaborating with an agentic AI-powered IDE to build software — is rapidly becoming a mainstream development approach. Tasks that once required weeks of engi...
Security code reviews increasingly rely on systems integrating Large Language Models (LLMs), ranging from interactive assistants to autonomous agents in CI/CD p...
'AI‑driven Autonomy & Internal Monitoring at OpenAI
Just use ChatGPT — sure, until your API bill hits $500/month. I've been running both local and cloud AI for over a year. Here are the real numbers. Cost Compari...
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Inferring the connectivity of neural circuits from incomplete observations is a fundamental challenge in neuroscience. We present a covariance-based method for ...
Large language models LLMs can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliabi...
MIT Researchers Use Generative AI to “See” Through Obstacles MIT researchers have spent more than a decade studying techniques that enable robots to find and m...
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A lot of people use LLMs as the source of their objective truth. They have a question that would be very well answered with a search leading to a reputable sour...
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OpenAI Accelerates Codex growth to power the next generation of Python developer tools Today we’re announcing that OpenAI will acquire Astralhttps://astral.sh/,...
After introducing last Augusthttps://9to5google.com/2025/08/13/gemini-personal-context/, Google might make the Gemini app’s Temporary chat feature much more pro...
Intracortical brain-computer interfaces (BCIs) can decode speech from neural activity with high accuracy when trained on data pooled across recording sessions. ...
This paper presents the constrained Hybrid Metaheuristic (cHM) algorithm as a general framework for continuous optimisation. Unlike many existing metaheuristics...
Overview I replicated David Ng's RYS methodhttps://dnhkng.github.io/posts/rys/ on consumer AMD GPUs RX 7900 XT + RX 6950 XT and discovered an unexpected behavi...
When developing AI applications, understanding the performance characteristics of different LLM API providers is crucial for making informed decisions. The API...
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Token pruning is essential for enhancing the computational efficiency of vision-language models (VLMs), particularly for video-based tasks where temporal redund...
Multimodal large language models (MLLMs) exhibit strong visual-language reasoning, yet remain confined to their native modalities and cannot directly process st...
Multimodal Large Language Models (MLLMs) have made impressive progress in connecting vision and language, but they still struggle with spatial understanding and...
In this work, we present EchoGen, a unified framework for layout-to-image generation and image grounding, capable of generating images with accurate layouts and...
Building LLM-based agents has become increasingly important. Recent works on LLM-based agent self-evolution primarily record successful experiences as textual p...
We present a training-free framework for continuous and controllable image editing at test time for text-conditioned generative models. In contrast to prior app...
Tokenization is a fundamental technique in the generative modeling of various modalities. In particular, it plays a critical role in autoregressive (AR) models,...
Synthesizing controllable 6-DOF object manipulation trajectories in 3D environments is essential for enabling robots to interact with complex scenes, yet remain...
Controlled video generation has seen drastic improvements in recent years. However, editing actions and dynamic events, or inserting contents that should affect...
Recent Multimodal Large Language Models (MLLMs) have shown high potential for spatial reasoning within 3D scenes. However, they typically rely on computationall...
Radar is a critical perception modality in autonomous driving systems due to its all-weather characteristics and ability to measure range and Doppler velocity. ...
Software vulnerabilities continue to grow in volume and remain difficult to detect in practice. Although learning-based vulnerability detection has progressed, ...
AI coding agents can resolve real-world software issues, yet they frequently introduce regressions, breaking tests that previously passed. Current benchmarks fo...
Orthogonalized-momentum optimizers such as Muon improve transformer training by approximately whitening/orthogonalizing matrix-valued momentum updates via a sho...
Robotics foundation models have demonstrated strong capabilities in executing natural language instructions across diverse tasks and environments. However, they...
Handling gender across languages remains a persistent challenge for Machine Translation (MT) and Large Language Models (LLMs), especially when translating from ...
