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🔍 Daily Picks in Interpretability & Analysis of LMs

Outstanding research in interpretability and evaluation of language models, summarized

Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models

Paper • 2412.16247 • Published 23 days ago • 1
Inferring Functionality of Attention Heads from their Parameters

Paper • 2412.11965 • Published 26 days ago • 2
LatentQA: Teaching LLMs to Decode Activations Into Natural Language

Paper • 2412.08686 • Published Dec 11, 2024 • 1
Training Large Language Models to Reason in a Continuous Latent Space

Paper • 2412.06769 • Published Dec 9, 2024 • 71

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 • 606
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

Patchscope: A Unifying Framework for Inspecting Hidden Representations of Language Models

Paper • 2401.06102 • Published Jan 11, 2024 • 20
Rethinking Interpretability in the Era of Large Language Models

Paper • 2402.01761 • Published Jan 30, 2024 • 22

Patchscope: A Unifying Framework for Inspecting Hidden Representations of Language Models

Paper • 2401.06102 • Published Jan 11, 2024 • 20

Patchscope: A Unifying Framework for Inspecting Hidden Representations of Language Models

Paper • 2401.06102 • Published Jan 11, 2024 • 20

Patchscope: A Unifying Framework for Inspecting Hidden Representations of Language Models

Paper • 2401.06102 • Published Jan 11, 2024 • 20

Understanding LLMs: A Comprehensive Overview from Training to Inference

Paper • 2401.02038 • Published Jan 4, 2024 • 62
DocLLM: A layout-aware generative language model for multimodal document understanding

Paper • 2401.00908 • Published Dec 31, 2023 • 181
LLaMA Beyond English: An Empirical Study on Language Capability Transfer

Paper • 2401.01055 • Published Jan 2, 2024 • 54
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning

Paper • 2401.01325 • Published Jan 2, 2024 • 27

The LLM Surgeon

Paper • 2312.17244 • Published Dec 28, 2023 • 9
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 66
Patchscope: A Unifying Framework for Inspecting Hidden Representations of Language Models

Paper • 2401.06102 • Published Jan 11, 2024 • 20
Model Surgery: Modulating LLM's Behavior Via Simple Parameter Editing

Paper • 2407.08770 • Published Jul 11, 2024 • 20

Alignment: FineTuning-Preference

S-LoRA: Serving Thousands of Concurrent LoRA Adapters

Paper • 2311.03285 • Published Nov 6, 2023 • 28
Tailoring Self-Rationalizers with Multi-Reward Distillation

Paper • 2311.02805 • Published Nov 6, 2023 • 3
Ultra-Long Sequence Distributed Transformer

Paper • 2311.02382 • Published Nov 4, 2023 • 2
OpenChat: Advancing Open-source Language Models with Mixed-Quality Data

Paper • 2309.11235 • Published Sep 20, 2023 • 16

Interpretability

A technical note on bilinear layers for interpretability

Paper • 2305.03452 • Published May 5, 2023 • 1
Interpreting Transformer's Attention Dynamic Memory and Visualizing the Semantic Information Flow of GPT

Paper • 2305.13417 • Published May 22, 2023 • 1
Explainable AI for Pre-Trained Code Models: What Do They Learn? When They Do Not Work?

Paper • 2211.12821 • Published Nov 23, 2022 • 1
The Linear Representation Hypothesis and the Geometry of Large Language Models

Paper • 2311.03658 • Published Nov 7, 2023 • 1

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