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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 601650 of 17610 papers

TitleStatusHype
Keeping Yourself is Important in Downstream Tuning Multimodal Large Language ModelCode2
Collaborative Expert LLMs Guided Multi-Objective Molecular OptimizationCode2
MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical EnvironmentsCode2
OptMetaOpenFOAM: Large Language Model Driven Chain of Thought for Sensitivity Analysis and Parameter Optimization based on CFDCode2
Forgetting Transformer: Softmax Attention with a Forget GateCode2
LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech EnhancementCode2
AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web PlatformsCode2
Rank1: Test-Time Compute for Reranking in Information RetrievalCode2
Citrus: Leveraging Expert Cognitive Pathways in a Medical Language Model for Advanced Medical Decision SupportCode2
SPECTRE: An FFT-Based Efficient Drop-In Replacement to Self-Attention for Long ContextsCode2
Introducing Visual Perception Token into Multimodal Large Language ModelCode2
A Training-free LLM-based Approach to General Chinese Character Error CorrectionCode2
TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton OperatorsCode2
TESS 2: A Large-Scale Generalist Diffusion Language ModelCode2
NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule GenerationCode2
UXAgent: An LLM Agent-Based Usability Testing Framework for Web DesignCode2
Continuous Diffusion Model for Language ModelingCode2
RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM GenerationCode2
Hierarchical Expert Prompt for Large-Language-Model: An Approach Defeat Elite AI in TextStarCraft II for the First TimeCode2
ViLa-MIL: Dual-scale Vision-Language Multiple Instance Learning for Whole Slide Image ClassificationCode2
WaferLLM: Large Language Model Inference at Wafer ScaleCode2
ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference OptimizationCode2
Reviving The Classics: Active Reward Modeling in Large Language Model AlignmentCode2
Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUsCode2
MetaOpenFOAM 2.0: Large Language Model Driven Chain of Thought for Automating CFD Simulation and Post-ProcessingCode2
AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse AutoencodersCode2
SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language ModelCode2
Fast Think-on-Graph: Wider, Deeper and Faster Reasoning of Large Language Model on Knowledge GraphCode2
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution FittingCode2
Agent-R: Training Language Model Agents to Reflect via Iterative Self-TrainingCode2
Advancing Language Model Reasoning through Reinforcement Learning and Inference ScalingCode2
Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic DesignCode2
LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal UnderstandingCode2
ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code GenerationCode2
UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission GenerationCode2
OpenOmni: Large Language Models Pivot Zero-shot Omnimodal Alignment across Language with Real-time Self-Aware Emotional Speech SynthesisCode2
Graph-Aware Isomorphic Attention for Adaptive Dynamics in TransformersCode2
Metadata Conditioning Accelerates Language Model Pre-trainingCode2
FLAME: Financial Large-Language Model Assessment and Metrics EvaluationCode2
Virgo: A Preliminary Exploration on Reproducing o1-like MLLMCode2
TrustRAG: Enhancing Robustness and Trustworthiness in RAGCode2
Dual Diffusion for Unified Image Generation and UnderstandingCode2
Vinci: A Real-time Embodied Smart Assistant based on Egocentric Vision-Language ModelCode2
RecLM: Recommendation Instruction TuningCode2
ETTA: Elucidating the Design Space of Text-to-Audio ModelsCode2
Long-Form Speech Generation with Spoken Language ModelsCode2
Large Language Model Safety: A Holistic SurveyCode2
Large Language Model Enhanced Recommender Systems: A SurveyCode2
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual DataCode2
Phi-4 Technical ReportCode2
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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