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🔍 Daily Picks in Interpretability & Analysis of LMs

Outstanding research in interpretability and evaluation of language models, summarized

Inferring Functionality of Attention Heads from their Parameters

Paper • 2412.11965 • Published 21 days ago • 2
LatentQA: Teaching LLMs to Decode Activations Into Natural Language

Paper • 2412.08686 • Published 26 days ago • 1
Training Large Language Models to Reason in a Continuous Latent Space

Paper • 2412.06769 • Published 28 days ago • 66
Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models

Paper • 2411.14257 • Published Nov 21, 2024 • 9

Interesting things.

AtP*: An efficient and scalable method for localizing LLM behaviour to components

Paper • 2403.00745 • Published Mar 1, 2024 • 12
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 605
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT

Paper • 2402.16840 • Published Feb 26, 2024 • 23
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Paper • 2402.13753 • Published Feb 21, 2024 • 114

graident optimization

AtP*: An efficient and scalable method for localizing LLM behaviour to components

Paper • 2403.00745 • Published Mar 1, 2024 • 12

Beyond Language Models: Byte Models are Digital World Simulators

Paper • 2402.19155 • Published Feb 29, 2024 • 49
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 52
VisionLLaMA: A Unified LLaMA Interface for Vision Tasks

Paper • 2403.00522 • Published Mar 1, 2024 • 44
Resonance RoPE: Improving Context Length Generalization of Large Language Models

Paper • 2403.00071 • Published Feb 29, 2024 • 22

Understanding LLM

A Language Model's Guide Through Latent Space

Paper • 2402.14433 • Published Feb 22, 2024 • 1
The Hidden Space of Transformer Language Adapters

Paper • 2402.13137 • Published Feb 20, 2024
Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language Models

Paper • 2402.16438 • Published Feb 26, 2024
AtP*: An efficient and scalable method for localizing LLM behaviour to components

Paper • 2403.00745 • Published Mar 1, 2024 • 12

DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14, 2024 • 26
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Paper • 2402.14905 • Published Feb 22, 2024 • 126
Resonance RoPE: Improving Context Length Generalization of Large Language Models

Paper • 2403.00071 • Published Feb 29, 2024 • 22
AtP*: An efficient and scalable method for localizing LLM behaviour to components

Paper • 2403.00745 • Published Mar 1, 2024 • 12

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 17
Transforming and Combining Rewards for Aligning Large Language Models

Paper • 2402.00742 • Published Feb 1, 2024 • 11
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Paper • 2402.03300 • Published Feb 5, 2024 • 76
Specialized Language Models with Cheap Inference from Limited Domain Data

Paper • 2402.01093 • Published Feb 2, 2024 • 45

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 52
Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28, 2024 • 18
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition

Paper • 2402.15220 • Published Feb 23, 2024 • 19
Linear Transformers are Versatile In-Context Learners

Paper • 2402.14180 • Published Feb 21, 2024 • 6

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