30 stories tagged with #transformers, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.
⌘ RSS feed for this tag → or search "Transformers"
Two Years Later, We’re Finally Learning How a Transformers-Inspired Rover Fared on the Moon
SORA-Q showed that tiny robots could do big things on the Moon.…
Practical NLP in the Browser with Transformers.js
This tutorial covers three NLP tasks: text classification, zero-shot labelling, and question answering using Transformers.js's pipeline() API.…
PrismML just released Binary and Ternary Bonsai Image 4B: 1-bit/ternary text-to-image diffusion transformers that can even run 100% locally in your browser on WebGPU.
Transformers Foundation Outlines Why Many Traceability Tools Fail to Meet the Standards of New Regulation
From TF-IDF to Transformers: Implementing Four Generations of Semantic Search
How did semantic search evolve from simple keyword matching into modern transformer-based language understanding? This hands-on article builds four generations of semantic search s…
Tensor Cache: Eviction-conditioned Associative Memory for Transformers
Autoregressive Transformer KV caches grow linearly with context length; sliding-window caching bounds memory but discards evicted tokens entirely, so relevant evidence outside the …
Every Component is a Lookup: Token Attribution and Composition from a Single Decomposition
Mechanistic interpretability of transformers requires identifying not just which components matter but how they compose into the computational route that produced a prediction. Bot…
SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers
Coda: Rewriting Transformer Blocks as GEMM-Epilogue Programs
Transformer training systems are built around dense linear algebra, yet a nontrivial fraction of end-to-end time is spent on surrounding memory-bound operators. Normalization, acti…
Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers
ANN-to-SNN conversion offers a practical, training-free route to spiking large language models. However, current pipelines primarily focus on spike-driven realizations for Transfor…
Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics
Transformers trained on modular arithmetic exhibit sharp transitions between memorization, generalization, and collapse. We show that weight decay acts as a scalar empirical contro…
Rethinking Cross-Layer Information Routing in Diffusion Transformers
Diffusion Transformers (DiTs) have become a de facto backbone of modern visual generation, and nearly every major axis of their design -- tokenization, attention, conditioning, obj…
Position: The Turing-Completeness of Real-World Autoregressive Transformers Relies Heavily on Context Management
Many works make the eye-catching claim that Transformers are Turing-complete. However, the literature often conflates two distinct settings: (i) a fixed Transformer system setting,…
Emergence of Frontier Superposition: M\"obius attractor and Cascade Supervision
Superposition allows Transformers to reason in depth, carrying an entire reasoning frontier in parallel through a bounded-depth forward pass instead of unrolling serial chain-of-th…
Precision Tracked Transformer via Kalman Filtering, Kriging and Process Noise
The Transformer is the foundational building block of modern AI, yet offers no principled handling of \emph{uncertainty}, which is prevalent in real applications: cold-start tokens…
Transformers Linearly Represent Highly Structured World Models
Do transformers, when trained on sequential reasoning traces, build internal models of the underlying task? And if so, does the structure of those internal representations mirror t…
From Sparsity to Simplicity: Enabling Simpler Sequential Replacements via Sparse Attention Distillation
Self-attention serves as the core foundation of large-scale transformer pretraining, but its quadratic token interaction cost makes inference expensive. Replacing attention with si…
I Tested KTransformers on My Laptop — 5 Hidden Features That Made 671B Models Actually Work 🔥
In May 2026, a GitHub project with 17,179 stars quietly achieved what cloud providers spend millions...…
KTransformers 的5个隐藏用法：671B模型在一台机器上跑出286 tokens/s 🔥
2026年5月，一个GitHub上仅有17,179颗星的开源项目，做到了各大云厂商砸了数百万美元才勉强做到的事情：在一台机器上以286...…
This Week Feels Like Christmas for Fans of ‘Transformers: The Movie’
'The Apology Tour' for the classic 1986 animated film continues with a few re-releases.…
Hasbro Is Celebrating 40 Years of ‘The Transformers: The Movie’ With ‘Reformatted’ Soundtrack — And Yes, Stan Bush Is Back
'Transformers: The Movie' at 40: New soundtrack taps Stan Bush, Sebastian Bach and more.…
[Day 7] Does Giving an AI More 'Thinking Time' Really Make It Smarter? Training an OpenMythos-Style Mini Model on DGX
Day 7 of my 100-experiment local LLM challenge. Trained a tiny OpenMythos-style mini model (theoretical reconstruction of the rumored Claude Mythos architecture) on multi-digit add…
Official 40th Anniversary Poster for ‘The Transformers: The Movie’ Returning to Theaters September 17
PaddleOCR 3.5: Running OCR and Document Parsing Tasks with a Transformers Backend
A Blog post by PaddlePaddle on Hugging Face…
‘Transformers’ Attraction to Launch in Brazil This Year as Hasbro Expands Global Experiences Biz (EXCLUSIVE)
A "Transformers" attraction will open in Brazil later this year, marking the latest live experience from toy giant Hasbro and a huge push into LATAM.…
Usual implementation of attention transformers (SDPA) is kind of bad, actually
The usual implementaiton of attention transformers (SDPA) is kind of bad, actually - antisdpa.md…
Grokking as Structural Inference: Transformers Need Bayesian Lottery Tickets
Why does a Transformer that has memorized its training set wait thousands of steps before it generalizes? Existing accounts locate this delay in norm minimization, feature emergenc…
Taming the Spike: Predicting Glucose Peaks 30 Minutes Ahead with Transformers and TensorFlow 🩸🚀
Managing blood glucose is like trying to drive a car where the steering wheel has a 20-minute lag....…
Autoregressive next token prediction and KV Cache in transformers
Understand the optimization technique in LLMs to speed up token generation…
Madras HC orders CBI probe into alleged money laundering in procuring transformers
The bench directed the State Directorate of Vigilance and Anti-Corruption (DVAC) that had been probing the matter until now, to “hand over” all papers and records related to the ca…