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🧠 Language Models
transformer architecture, fine-tuning, pretraining, RLHF
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186578
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Language Models
🧠
LLMs
calcifercomputing.com
·
2d
·
Hacker News
Fine-Grained
Analysis of Shared
Syntactic
Mechanisms in Language Models
🧠
LLMs
arxiv.org
·
3d
Reinforcement
fine-tuning
with LLM-as-a-judge
🧠
LLMs
aws.amazon.com
·
5h
epscylonb/1386.ai.rocm
: A lightweight transformer language model built from scratch in PyTorch, trained on a single consumer GPU with a full pipeline for data processing, pretraining, and instruction tuning.
🧠
LLMs
github.com
·
2d
·
Hacker News
Zero-Cost Transparent
Semiotic
Awareness for Frozen Language Models
SRT-Adapter
🔎
AI Interpretability
sublius.substack.com
·
4d
·
Substack
Training language models to be warm can reduce
accuracy
and increase
sycophancy
🧠
LLMs
nature.com
·
1d
Introspection
Adapters
: Training LLMs to Report Their Learned Behaviors
🧠
LLMs
lesswrong.com
·
2d
Pretrain
vs
Fine-Tune
✅
Dev Best Practices
byhand.ai
·
6d
How the Next Generation of AI Models are Going to
Completely
Change AI
Inference
🔬
AI Research
artificialintelligencemadesimple.com
·
1d
Watch language models think.
⚙️
MLOps
openinterp.org
·
6d
·
Hacker News
Flow
generation through natural language: An agentic
modeling
approach (11 minute read)
🤖
AI Engineering
shopify.engineering
·
1d
Announcing
Together AI and
Adaption
Partnership
🤖
AI Engineering
together.ai
·
1d
A Deep
Layer
Limit Analysis of
Transformer
🧠
LLMs
global-sci.com
·
3d
Back to
BERT
in 2026:
ModernGENA
as a Strong, Efficient Baseline for DNA Foundation Models
🧠
LLMs
biorxiv.org
·
5d
Fixing
What LLMs Get Wrong (22 minute read)
🧠
LLMs
thebigdataguy.substack.com
·
4d
·
Substack
RAG vs.
Fine-Tuning
vs.
Prompting
: 2026 Strategic Guide
✍️
Prompt Engineering
endevsols.com
·
4d
·
DEV
Honey
, I
Shrunk
the Coding Agent
⚙️
MLOps
itayinbarr.substack.com
·
5d
·
Substack
TurboQuant
: A First-Principles
Walkthrough
✅
Formal Verification
taoofmac.com
·
3d
Libraries
and
Archives
, a Natural Home for Language Models
🧠
LLMs
rsdoiel.github.io
·
5d
Adaptive and Fine-grained Module-wise Expert Pruning for Efficient
LoRA-MoE
Fine-Tuning
⚙️
MLOps
arxiv.org
·
21h
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