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MMLU

Papers

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Showing 101–125 of 340 papers

TitleStatusHype
Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning—0
Step-wise Policy for Rare-tool Knowledge (SPaRK): Offline RL that Drives Diverse Tool Use in LLMsCode0
Lizard: An Efficient Linearization Framework for Large Language Models—0
Integrating External Tools with Large Language Models to Improve Accuracy—0
Growing Transformers: Modular Composition and Layer-wise Expansion on a Frozen SubstrateCode0
Emergent Semantics Beyond Token Embeddings: Transformer LMs with Frozen Visual Unicode RepresentationsCode0
Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training—0
Multi-lingual Functional Evaluation for Large Language Models—0
Enterprise Large Language Model Evaluation Benchmark—0
Biomed-Enriched: A Biomedical Dataset Enriched with LLMs for Pretraining and Extracting Rare and Hidden Content—0
Gazal-R1: Achieving State-of-the-Art Medical Reasoning with Parameter-Efficient Two-Stage Training—0
Slimming Down LLMs Without Losing Their Minds—0
Surface Fairness, Deep Bias: A Comparative Study of Bias in Language Models—0
MoE-GPS: Guidlines for Prediction Strategy for Dynamic Expert Duplication in MoE Load Balancing—0
From Threat to Tool: Leveraging Refusal-Aware Injection Attacks for Safety Alignment—0
Automatic Robustness Stress Testing of LLMs as Mathematical Problem Solvers—0
GEM: Empowering LLM for both Embedding Generation and Language Understanding—0
Do Language Models Mirror Human Confidence? Exploring Psychological Insights to Address Overconfidence in LLMsCode0
Simulating Training Data Leakage in Multiple-Choice Benchmarks for LLM EvaluationCode0
Model Unlearning via Sparse Autoencoder Subspace Guided Projections—0
Revisiting Uncertainty Estimation and Calibration of Large Language Models—0
DyePack: Provably Flagging Test Set Contamination in LLMs Using BackdoorsCode0
Actor-Critic based Online Data Mixing For Language Model Pre-Training—0
Large Language Models Often Know When They Are Being Evaluated—0
Capability-Based Scaling Laws for LLM Red-TeamingCode0
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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