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SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Paper β’ 2509.22944 β’ Published β’ 79 -
Robot Learning: A Tutorial
Paper β’ 2510.12403 β’ Published β’ 114 -
UniMoE-Audio: Unified Speech and Music Generation with Dynamic-Capacity MoE
Paper β’ 2510.13344 β’ Published β’ 62 -
Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understanding
Paper β’ 2510.06308 β’ Published β’ 53
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Collections including paper arxiv:2509.22944
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Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper β’ 2508.03680 β’ Published β’ 121 -
HumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistants
Paper β’ 2509.08494 β’ Published β’ 1 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper β’ 2508.16153 β’ Published β’ 158 -
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Paper β’ 2509.22944 β’ Published β’ 79
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What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Paper β’ 2509.19284 β’ Published β’ 22 -
Soft Tokens, Hard Truths
Paper β’ 2509.19170 β’ Published β’ 15 -
CompLLM: Compression for Long Context Q&A
Paper β’ 2509.19228 β’ Published β’ 8 -
Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
Paper β’ 2509.06861 β’ Published β’ 8
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Outlier-Safe Pre-Training for Robust 4-Bit Quantization of Large Language Models
Paper β’ 2506.19697 β’ Published β’ 44 -
Winning the Pruning Gamble: A Unified Approach to Joint Sample and Token Pruning for Efficient Supervised Fine-Tuning
Paper β’ 2509.23873 β’ Published β’ 67 -
Efficient Multi-modal Large Language Models via Progressive Consistency Distillation
Paper β’ 2510.00515 β’ Published β’ 39 -
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Paper β’ 2509.22944 β’ Published β’ 79
-
Repo duplicator
π»320Duplicate Hugging Face repositories
-
Open ASR Leaderboard
π1.15kDisplay and request speech recognition model benchmarks
-
NousResearch/Minos-v1
Text Classification β’ 0.4B β’ Updated β’ 1.99k β’ β’ 166 -
Parakeet-TDT-0.6b-V2
Β449Transcribe audio to text with timestamps
-
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Paper β’ 2509.22944 β’ Published β’ 79 -
Robot Learning: A Tutorial
Paper β’ 2510.12403 β’ Published β’ 114 -
UniMoE-Audio: Unified Speech and Music Generation with Dynamic-Capacity MoE
Paper β’ 2510.13344 β’ Published β’ 62 -
Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understanding
Paper β’ 2510.06308 β’ Published β’ 53
-
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Paper β’ 2509.19284 β’ Published β’ 22 -
Soft Tokens, Hard Truths
Paper β’ 2509.19170 β’ Published β’ 15 -
CompLLM: Compression for Long Context Q&A
Paper β’ 2509.19228 β’ Published β’ 8 -
Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
Paper β’ 2509.06861 β’ Published β’ 8
-
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper β’ 2508.03680 β’ Published β’ 121 -
HumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistants
Paper β’ 2509.08494 β’ Published β’ 1 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper β’ 2508.16153 β’ Published β’ 158 -
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Paper β’ 2509.22944 β’ Published β’ 79
-
Outlier-Safe Pre-Training for Robust 4-Bit Quantization of Large Language Models
Paper β’ 2506.19697 β’ Published β’ 44 -
Winning the Pruning Gamble: A Unified Approach to Joint Sample and Token Pruning for Efficient Supervised Fine-Tuning
Paper β’ 2509.23873 β’ Published β’ 67 -
Efficient Multi-modal Large Language Models via Progressive Consistency Distillation
Paper β’ 2510.00515 β’ Published β’ 39 -
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Paper β’ 2509.22944 β’ Published β’ 79
-
Repo duplicator
π»320Duplicate Hugging Face repositories
-
Open ASR Leaderboard
π1.15kDisplay and request speech recognition model benchmarks
-
NousResearch/Minos-v1
Text Classification β’ 0.4B β’ Updated β’ 1.99k β’ β’ 166 -
Parakeet-TDT-0.6b-V2
Β449Transcribe audio to text with timestamps