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MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 21 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 17 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 16 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31
Collections
Discover the best community collections!
Collections including paper arxiv:2509.04292
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 625 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 298 -
Group Sequence Policy Optimization
Paper • 2507.18071 • Published • 306 -
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth
Paper • 2509.03867 • Published • 208
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Seed-Coder: Let the Code Model Curate Data for Itself
Paper • 2506.03524 • Published • 6 -
Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning
Paper • 2504.13914 • Published • 4 -
FlowTok: Flowing Seamlessly Across Text and Image Tokens
Paper • 2503.10772 • Published • 19 -
UVE: Are MLLMs Unified Evaluators for AI-Generated Videos?
Paper • 2503.09949 • Published • 5
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Contrastive Learning for Many-to-many Multilingual Neural Machine Translation
Paper • 2105.09501 • Published -
Cross-modal Contrastive Learning for Speech Translation
Paper • 2205.02444 • Published -
ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs
Paper • 2210.03052 • Published -
Diffusion Glancing Transformer for Parallel Sequence to Sequence Learning
Paper • 2212.10240 • Published • 1
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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Open Data Synthesis For Deep Research
Paper • 2509.00375 • Published • 68 -
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
Paper • 2509.03403 • Published • 21 -
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations
Paper • 2509.03405 • Published • 23 -
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs
Paper • 2509.00930 • Published • 4
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DeepSeek-R1 Thoughtology: Let's <think> about LLM Reasoning
Paper • 2504.07128 • Published • 86 -
BM25S: Orders of magnitude faster lexical search via eager sparse scoring
Paper • 2407.03618 • Published • 13 -
Deep Think with Confidence
Paper • 2508.15260 • Published • 87 -
R-Zero: Self-Evolving Reasoning LLM from Zero Data
Paper • 2508.05004 • Published • 126
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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 249 • 96 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
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PopAlign: Diversifying Contrasting Patterns for a More Comprehensive Alignment
Paper • 2410.13785 • Published • 19 -
Aligning Large Language Models via Self-Steering Optimization
Paper • 2410.17131 • Published • 24 -
Baichuan Alignment Technical Report
Paper • 2410.14940 • Published • 51 -
SemiEvol: Semi-supervised Fine-tuning for LLM Adaptation
Paper • 2410.14745 • Published • 47
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MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 21 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 17 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 16 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31
-
Open Data Synthesis For Deep Research
Paper • 2509.00375 • Published • 68 -
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
Paper • 2509.03403 • Published • 21 -
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations
Paper • 2509.03405 • Published • 23 -
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs
Paper • 2509.00930 • Published • 4
-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 625 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 298 -
Group Sequence Policy Optimization
Paper • 2507.18071 • Published • 306 -
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth
Paper • 2509.03867 • Published • 208
-
DeepSeek-R1 Thoughtology: Let's <think> about LLM Reasoning
Paper • 2504.07128 • Published • 86 -
BM25S: Orders of magnitude faster lexical search via eager sparse scoring
Paper • 2407.03618 • Published • 13 -
Deep Think with Confidence
Paper • 2508.15260 • Published • 87 -
R-Zero: Self-Evolving Reasoning LLM from Zero Data
Paper • 2508.05004 • Published • 126
-
Seed-Coder: Let the Code Model Curate Data for Itself
Paper • 2506.03524 • Published • 6 -
Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning
Paper • 2504.13914 • Published • 4 -
FlowTok: Flowing Seamlessly Across Text and Image Tokens
Paper • 2503.10772 • Published • 19 -
UVE: Are MLLMs Unified Evaluators for AI-Generated Videos?
Paper • 2503.09949 • Published • 5
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 249 • 96 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
Contrastive Learning for Many-to-many Multilingual Neural Machine Translation
Paper • 2105.09501 • Published -
Cross-modal Contrastive Learning for Speech Translation
Paper • 2205.02444 • Published -
ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs
Paper • 2210.03052 • Published -
Diffusion Glancing Transformer for Parallel Sequence to Sequence Learning
Paper • 2212.10240 • Published • 1
-
PopAlign: Diversifying Contrasting Patterns for a More Comprehensive Alignment
Paper • 2410.13785 • Published • 19 -
Aligning Large Language Models via Self-Steering Optimization
Paper • 2410.17131 • Published • 24 -
Baichuan Alignment Technical Report
Paper • 2410.14940 • Published • 51 -
SemiEvol: Semi-supervised Fine-tuning for LLM Adaptation
Paper • 2410.14745 • Published • 47
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25