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🔍 Daily Picks in Interpretability & Analysis of LMs

Outstanding research in interpretability and evaluation of language models, summarized

Calibrating Reasoning in Language Models with Internal Consistency

Paper • 2405.18711 • Published 4 days ago • 1
Emergence of a High-Dimensional Abstraction Phase in Language Transformers

Paper • 2405.15471 • Published 9 days ago • 1
Not All Language Model Features Are Linear

Paper • 2405.14860 • Published 9 days ago • 33
Your Transformer is Secretly Linear

Paper • 2405.12250 • Published 13 days ago • 134

Large Language Model (LLM) and NLP related papers.

LoRA+: Efficient Low Rank Adaptation of Large Models

Paper • 2402.12354 • Published Feb 19 • 5
The FinBen: An Holistic Financial Benchmark for Large Language Models

Paper • 2402.12659 • Published Feb 20 • 13
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization

Paper • 2402.13249 • Published Feb 20 • 10
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10 • 62

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1 • 20
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1 • 76
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 135
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30 • 22

Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11 • 80
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

Paper • 2404.10667 • Published Apr 16 • 12
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20 • 25
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14 • 21

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 74

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 74

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 74

papers-efficiency

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2 • 102
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 74

Papers - Fine-tuning - Report - Llama 7B and 13B

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 74

Papers - Fine-tuning - ReFT

In this paper, we propose a strong alternative to PEFTs, LoReFT. LoReFT achieves strong per- formance across benchmarks from four domains while being

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 74

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