Igor Molybog
igormolybog
AI & ML interests
Optimization, Machine Learning
Organizations
None yet
llama + WebWork
Solver training
-
Language Models can be Logical Solvers
Paper • 2311.06158 • Published • 23 -
SymbolicAI: A framework for logic-based approaches combining generative models and solvers
Paper • 2402.00854 • Published • 22 -
Grandmaster-Level Chess Without Search
Paper • 2402.04494 • Published • 69 -
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping
Paper • 2402.14083 • Published • 48
Reasoning
-
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer
Paper • 2311.06720 • Published • 9 -
System 2 Attention (is something you might need too)
Paper • 2311.11829 • Published • 44 -
TinyGSM: achieving >80% on GSM8k with small language models
Paper • 2312.09241 • Published • 40 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 31
Long context
-
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 146 -
SparQ Attention: Bandwidth-Efficient LLM Inference
Paper • 2312.04985 • Published • 40 -
Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models
Paper • 2401.04658 • Published • 27 -
E^2-LLM: Efficient and Extreme Length Extension of Large Language Models
Paper • 2401.06951 • Published • 26
Agents
Scaling laws
-
Scaling Laws for Downstream Task Performance of Large Language Models
Paper • 2402.04177 • Published • 20 -
A Tale of Tails: Model Collapse as a Change of Scaling Laws
Paper • 2402.07043 • Published • 16 -
Scaling Laws for Fine-Grained Mixture of Experts
Paper • 2402.07871 • Published • 14 -
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 26
robotics
Imagen
Inference speed
-
FlashDecoding++: Faster Large Language Model Inference on GPUs
Paper • 2311.01282 • Published • 37 -
Co-training and Co-distillation for Quality Improvement and Compression of Language Models
Paper • 2311.02849 • Published • 8 -
Prompt Cache: Modular Attention Reuse for Low-Latency Inference
Paper • 2311.04934 • Published • 34 -
Exponentially Faster Language Modelling
Paper • 2311.10770 • Published • 119
evals
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Holistic Evaluation of Text-To-Image Models
Paper • 2311.04287 • Published • 16 -
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks
Paper • 2311.07463 • Published • 15 -
Trusted Source Alignment in Large Language Models
Paper • 2311.06697 • Published • 12 -
DiLoCo: Distributed Low-Communication Training of Language Models
Paper • 2311.08105 • Published • 16
Datasets
-
Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models
Paper • 2311.06783 • Published • 28 -
To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning
Paper • 2311.07574 • Published • 16 -
Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding
Paper • 2401.04575 • Published • 17 -
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Paper • 2402.00159 • Published • 65
Hetero training
Open
-
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models
Paper • 2402.01739 • Published • 28 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 71 -
Poro 34B and the Blessing of Multilinguality
Paper • 2404.01856 • Published • 15
LM economy
-
Specialized Language Models with Cheap Inference from Limited Domain Data
Paper • 2402.01093 • Published • 47 -
Computing Power and the Governance of Artificial Intelligence
Paper • 2402.08797 • Published • 15 -
Understanding LLMs: A Comprehensive Overview from Training to Inference
Paper • 2401.02038 • Published • 65
compression
-
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 22 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 50 -
GPTVQ: The Blessing of Dimensionality for LLM Quantization
Paper • 2402.15319 • Published • 22
Alignment
Domain spec fine-tuning
Inference speed
-
FlashDecoding++: Faster Large Language Model Inference on GPUs
Paper • 2311.01282 • Published • 37 -
Co-training and Co-distillation for Quality Improvement and Compression of Language Models
Paper • 2311.02849 • Published • 8 -
Prompt Cache: Modular Attention Reuse for Low-Latency Inference
Paper • 2311.04934 • Published • 34 -
Exponentially Faster Language Modelling
Paper • 2311.10770 • Published • 119
llama + WebWork
evals
-
Holistic Evaluation of Text-To-Image Models
Paper • 2311.04287 • Published • 16 -
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks
Paper • 2311.07463 • Published • 15 -
Trusted Source Alignment in Large Language Models
Paper • 2311.06697 • Published • 12 -
DiLoCo: Distributed Low-Communication Training of Language Models
Paper • 2311.08105 • Published • 16
Solver training
-
Language Models can be Logical Solvers
Paper • 2311.06158 • Published • 23 -
SymbolicAI: A framework for logic-based approaches combining generative models and solvers
Paper • 2402.00854 • Published • 22 -
Grandmaster-Level Chess Without Search
Paper • 2402.04494 • Published • 69 -
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping
Paper • 2402.14083 • Published • 48
Datasets
-
Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models
Paper • 2311.06783 • Published • 28 -
To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning
Paper • 2311.07574 • Published • 16 -
Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding
Paper • 2401.04575 • Published • 17 -
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Paper • 2402.00159 • Published • 65
Reasoning
-
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer
Paper • 2311.06720 • Published • 9 -
System 2 Attention (is something you might need too)
Paper • 2311.11829 • Published • 44 -
TinyGSM: achieving >80% on GSM8k with small language models
Paper • 2312.09241 • Published • 40 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 31
Hetero training
Long context
-
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 146 -
SparQ Attention: Bandwidth-Efficient LLM Inference
Paper • 2312.04985 • Published • 40 -
Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models
Paper • 2401.04658 • Published • 27 -
E^2-LLM: Efficient and Extreme Length Extension of Large Language Models
Paper • 2401.06951 • Published • 26
Open
-
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models
Paper • 2402.01739 • Published • 28 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 71 -
Poro 34B and the Blessing of Multilinguality
Paper • 2404.01856 • Published • 15
Agents
LM economy
-
Specialized Language Models with Cheap Inference from Limited Domain Data
Paper • 2402.01093 • Published • 47 -
Computing Power and the Governance of Artificial Intelligence
Paper • 2402.08797 • Published • 15 -
Understanding LLMs: A Comprehensive Overview from Training to Inference
Paper • 2401.02038 • Published • 65
Scaling laws
-
Scaling Laws for Downstream Task Performance of Large Language Models
Paper • 2402.04177 • Published • 20 -
A Tale of Tails: Model Collapse as a Change of Scaling Laws
Paper • 2402.07043 • Published • 16 -
Scaling Laws for Fine-Grained Mixture of Experts
Paper • 2402.07871 • Published • 14 -
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 26
compression
-
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 22 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 50 -
GPTVQ: The Blessing of Dimensionality for LLM Quantization
Paper • 2402.15319 • Published • 22
robotics
Alignment
Imagen