SOTAVerified

Language Modelling

A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.

Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.

Source: Wikipedia

Papers

Showing 13011350 of 17610 papers

TitleStatusHype
Well-Read Students Learn Better: On the Importance of Pre-training Compact ModelsCode2
Knowledge Representation Learning: A Quantitative ReviewCode2
Training RNNs as Fast as CNNsCode2
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts LayerCode2
End-To-End Memory NetworksCode2
Describe Anything Model for Visual Question Answering on Text-rich ImagesCode1
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofingCode1
Differential MambaCode1
Evaluating Morphological Alignment of Tokenizers in 70 LanguagesCode1
GPTailor: Large Language Model Pruning Through Layer Cutting and StitchingCode1
LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling ResearchCode1
Sampling from Your Language Model One Byte at a TimeCode1
RMIT-ADM+S at the SIGIR 2025 LiveRAG ChallengeCode1
SeqPE: Transformer with Sequential Position EncodingCode1
TagRouter: Learning Route to LLMs through Tags for Open-Domain Text Generation TasksCode1
Diffusion Sequence Models for Enhanced Protein Representation and GenerationCode1
Towards Universal Offline Black-Box Optimization via Learning Language Model EmbeddingsCode1
SAFE: Finding Sparse and Flat Minima to Improve PruningCode1
DAM: Dynamic Attention Mask for Long-Context Large Language Model Inference AccelerationCode1
OpenMaskDINO3D : Reasoning 3D Segmentation via Large Language ModelCode1
POSS: Position Specialist Generates Better Draft for Speculative DecodingCode1
Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series ForecastingCode1
Period-LLM: Extending the Periodic Capability of Multimodal Large Language ModelCode1
VCapsBench: A Large-scale Fine-grained Benchmark for Video Caption Quality EvaluationCode1
Uni-MuMER: Unified Multi-Task Fine-Tuning of Vision-Language Model for Handwritten Mathematical Expression RecognitionCode1
ChatCFD: an End-to-End CFD Agent with Domain-specific Structured ThinkingCode1
REAL-Prover: Retrieval Augmented Lean Prover for Mathematical ReasoningCode1
Pretraining Language Models to Ponder in Continuous SpaceCode1
CogniBench: A Legal-inspired Framework and Dataset for Assessing Cognitive Faithfulness of Large Language ModelsCode1
REARANK: Reasoning Re-ranking Agent via Reinforcement LearningCode1
Unifying Multimodal Large Language Model Capabilities and Modalities via Model MergingCode1
Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM CompressionCode1
ScreenExplorer: Training a Vision-Language Model for Diverse Exploration in Open GUI WorldCode1
Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target AtomsCode1
Decoupled Visual Interpretation and Linguistic Reasoning for Math Problem SolvingCode1
Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across ModalitiesCode1
RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement LearningCode1
ChemMLLM: Chemical Multimodal Large Language ModelCode1
A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial OptimizationCode1
Speculative Decoding Reimagined for Multimodal Large Language ModelsCode1
U-SAM: An audio language Model for Unified Speech, Audio, and Music UnderstandingCode1
3D Visual Illusion Depth EstimationCode1
R3: Robust Rubric-Agnostic Reward ModelsCode1
Unifying Segment Anything in Microscopy with Multimodal Large Language ModelCode1
Sample Efficient Reinforcement Learning via Large Vision Language Model DistillationCode1
Multi-Token Prediction Needs RegistersCode1
ImagineBench: Evaluating Reinforcement Learning with Large Language Model RolloutsCode1
Extending Large Vision-Language Model for Diverse Interactive Tasks in Autonomous DrivingCode1
Kalman Filter Enhanced GRPO for Reinforcement Learning-Based Language Model ReasoningCode1
Symbolic Regression with Multimodal Large Language Models and Kolmogorov Arnold NetworksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified