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MMLU

Papers

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Showing 151–175 of 340 papers

TitleStatusHype
Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs—0
Bridging the Gap: Enhancing LLM Performance for Low-Resource African Languages with New Benchmarks, Fine-Tuning, and Cultural AdjustmentsCode1
Nanoscaling Floating-Point (NxFP): NanoMantissa, Adaptive Microexponents, and Code Recycling for Direct-Cast Compression of Large Language Models—0
Llama 3 Meets MoE: Efficient Upcycling—0
LLM Distillation for Efficient Few-Shot Multiple Choice Question Answering—0
HadaCore: Tensor Core Accelerated Hadamard Transform KernelCode3
Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation—0
Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset—0
The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?—0
Noise Injection Reveals Hidden Capabilities of Sandbagging Language ModelsCode0
Improving Physics Reasoning in Large Language Models Using Mixture of Refinement Agents—0
Simple and Provable Scaling Laws for the Test-Time Compute of Large Language Models—0
Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference—0
Predicting Emergent Capabilities by Finetuning—0
Learning from "Silly" Questions Improves Large Language Models, But Only Slightly—0
GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs—0
Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models—0
Reasoning Robustness of LLMs to Adversarial Typographical Errors—0
Watson: A Cognitive Observability Framework for the Reasoning of LLM-Powered Agents—0
TODO: Enhancing LLM Alignment with Ternary PreferencesCode0
Project MPG: towards a generalized performance benchmark for LLM capabilities—0
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language ModelsCode1
Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-DesignCode1
LOGO -- Long cOntext aliGnment via efficient preference OptimizationCode1
Adaptive Dense Reward: Understanding the Gap Between Action and Reward Space in Alignment—0
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All datasetsSIOP 2020/2021MMLU-ProVCTK

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1go ahead, make my dataFinal_score61.72—Unverified
2#GreedyCowFinal_score61.63—Unverified
3Don't Ask Us yFinal_score61.4—Unverified
4Data_and_ConfusedFinal_score60.96—Unverified
5raakaFinal_score60.91—Unverified
6WafflesFinal_score60.91—Unverified
7Team ProcrustinationFinal_score60.64—Unverified
8Axiom Consulting PartnersFinal_score60.63—Unverified
9Lets_Be_FairFinal_score60.23—Unverified
10goonersFinal_score60.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Orange-mini0-shot MRR99.19—Unverified
#ModelMetricClaimedVerifiedStatus
1HybridBeam+SI-SDRi13.3—Unverified