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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 13511400 of 17610 papers

TitleStatusHype
MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from TextbooksCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
Nesterov Method for Asynchronous Pipeline Parallel OptimizationCode1
WirelessAgent: Large Language Model Agents for Intelligent Wireless NetworksCode1
Visual Test-time Scaling for GUI Agent GroundingCode1
MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model FrameworkCode1
Reviving Any-Subset Autoregressive Models with Principled Parallel Sampling and Speculative DecodingCode1
PhenoAssistant: A Conversational Multi-Agent AI System for Automated Plant PhenotypingCode1
LEAM: A Prompt-only Large Language Model-enabled Antenna Modeling MethodCode1
LongMamba: Enhancing Mamba's Long Context Capabilities via Training-Free Receptive Field EnlargementCode1
Walk the Talk? Measuring the Faithfulness of Large Language Model ExplanationsCode1
Learning to Attribute with AttentionCode1
SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical ImagingCode1
Fine-tuning a Large Language Model for Automating Computational Fluid Dynamics SimulationsCode1
Parameterized Synthetic Text Generation with SimpleStoriesCode1
LauraTSE: Target Speaker Extraction using Auto-Regressive Decoder-Only Language ModelsCode1
Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM CollaborationCode1
Hessian of Perplexity for Large Language Models by PyTorch autograd (Open Source)Code1
CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial OptimizationCode1
MSL: Not All Tokens Are What You Need for Tuning LLM as a RecommenderCode1
Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-GenerationCode1
Distillation and Refinement of Reasoning in Small Language Models for Document Re-rankingCode1
SARLANG-1M: A Benchmark for Vision-Language Modeling in SAR Image UnderstandingCode1
Beyond the Next Token: Towards Prompt-Robust Zero-Shot Classification via Efficient Multi-Token PredictionCode1
Language Models Are Implicitly ContinuousCode1
STING-BEE: Towards Vision-Language Model for Real-World X-ray Baggage Security InspectionCode1
MG-MotionLLM: A Unified Framework for Motion Comprehension and Generation across Multiple GranularitiesCode1
IPA-CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology and Phonemic Language ModelingCode1
JailDAM: Jailbreak Detection with Adaptive Memory for Vision-Language ModelCode1
STPNet: Scale-aware Text Prompt Network for Medical Image SegmentationCode1
Representation Bending for Large Language Model SafetyCode1
TiC-LM: A Web-Scale Benchmark for Time-Continual LLM PretrainingCode1
Rethinking Key-Value Cache Compression Techniques for Large Language Model ServingCode1
CrowdVLM-R1: Expanding R1 Ability to Vision Language Model for Crowd Counting using Fuzzy Group Relative Policy RewardCode1
Imagine All The Relevance: Scenario-Profiled Indexing with Knowledge Expansion for Dense RetrievalCode1
BOLT: Boost Large Vision-Language Model Without Training for Long-form Video UnderstandingCode1
OpenHuEval: Evaluating Large Language Model on Hungarian SpecificsCode1
CAFe: Unifying Representation and Generation with Contrastive-Autoregressive FinetuningCode1
CoLLM: A Large Language Model for Composed Image RetrievalCode1
LogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy PreservationCode1
PM4Bench: A Parallel Multilingual Multi-Modal Multi-task Benchmark for Large Vision Language ModelCode1
Sun-Shine: A Large Language Model for Tibetan CultureCode1
Language Model Uncertainty Quantification with Attention ChainCode1
What Makes a Reward Model a Good Teacher? An Optimization PerspectiveCode1
Does Your Vision-Language Model Get Lost in the Long Video Sampling Dilemma?Code1
CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal ControlCode1
Open3DVQA: A Benchmark for Comprehensive Spatial Reasoning with Multimodal Large Language Model in Open SpaceCode1
MMS-LLaMA: Efficient LLM-based Audio-Visual Speech Recognition with Minimal Multimodal Speech TokensCode1
BiasEdit: Debiasing Stereotyped Language Models via Model EditingCode1
EvalTree: Profiling Language Model Weaknesses via Hierarchical Capability TreesCode1
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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