TMLR Published Papers

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TMLR Homepage: https://jmlr.org/tmlr/ TMLR Infinite Conference: https://tmlr.infinite-conf.org/

VColRL: Learn to solve the Vertex Coloring Problem using Reinforcement Learning
On the Role of Discrete Representation in Sparse Mixture of Experts
Node-Level Data Valuation on Graphs
Do Think Tags Really Help LLMs Plan? A Critical Evaluation of ReAct-Style Prompting
Taxonomy, Opportunities, and Challenges of Representation Engineering for Large Language Models
NeoBERT: A Next Generation BERT
SR-Reward: Taking The Path More Traveled
Exploring and Improving Initialization for Deep Graph Neural Networks: A Signal Propagation Perspect...
LLM-Guided Self-Supervised Tabular Learning With Task-Specific Pre-text Tasks
Effect of Random Learning Rate: Theoretical Analysis of SGD Dynamics in Non-Convex Optimization via ...
Metamorphic Forward Adaptation Network: Dynamically Adaptive and Modular Multi-layer Learning
Illustrated Landmark Graphs for Long-horizon Policy Learning
Mind the truncation gap: challenges of learning on dynamic graphs with recurrent architectures
GenCAD: Image-Conditioned Computer-Aided Design Generation with Transformer-Based Contrastive Repres...
TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis
Interactive Task Planning with Language Models
MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection
Explaining Node Embeddings
Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Bal...
PLUM: Improving Inference Efficiency By Leveraging Repetition-Sparsity Trade-Off
Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building
DiffSampling: Enhancing Diversity and Accuracy in Neural Text Generation
CADmium: Fine-Tuning Code Language Models for Text- Driven Sequential CAD Design
On a Gradient Approach to Chebyshev Center Problems with Applications to Function Learning
CREW-Wildfire: Benchmarking Agentic Multi-Agent Collaborations at Scale
Uncovering the Computational Roles of Nonlinearity in Sequence Modeling Using Almost-Linear RNNs
PredLDM: Spatiotemporal Sequence Prediction with Latent Diffusion Models
Tabby: A Language Model Architecture for Tabular and Structured Data Synthesis
DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-view CBCT Reconstruction
Generative Proto-Sequence: Sequence-Level Decision Making for Long-Horizon Reinforcement Learning
iiANET: Inception Inspired Attention Hybrid Network for efficient Long-Range Dependency
Exploring exploration with foundation agents in interactive environments
Rethinking Memory in Continual Learning: Beyond a Monolithic Store of the Past
Physics of Language Models: Part 1, Learning Hierarchical Language Structures
On the Expressiveness of Softmax Attention: A Recurrent Neural Network Perspective
Multi-BK-Net: Multi-Branch Multi-Kernel Convolutional Neural Networks for Clinical EEG Analysis
FedDUAL: A Dual-Strategy with Adaptive Loss and Dynamic Aggregation for Mitigating Data Heterogeneit...
TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scen...
Robust Weight Imprinting: Insights from Neural Collapse and Proxy-Based Aggregation
Is There a Better Source Distribution than Gaussian? Exploring Source Distributions for Image Flow M...
Comprehension Without Competence: Architectural Limits of LLMs in Symbolic Computation and Reasoning
Learning to Rank Features to Enhance Graph Neural Networks for Graph Classification
Noise-Aware Adaptation of Pre-trained Foundation Models for Single-photon Image Classification
The Choice of Normalization Influences Shrinkage in Regularized Regression
Early Classification of Time Series: A Survey and Benchmark
Coreset-Driven Re-Labeling: Tackling Noisy Annotations with Noise-Free Gradients
Let Your Light Shine: Foreground Portrait Matting via Deep Flash Priors
Robust Multimodal Learning via Cross-Modal Proxy Tokens
Learning to Be Cautious
Towards Formalizing Spuriousness of Biased Datasets Using Partial Information Decomposition
Before Forgetting, There's Learning: Representation Learning Challenges in Online Unsupervised Conti...
Unlearning Misalignment for Personalized LLM Adaptation via Instance-Response-Dependent Discrepancie...
Pre-Training Representations of Binary Code Using Contrastive Learning
What Time Tells Us? An Explorative Study of Time Awareness Learned from Static Images
Pref-GUIDE: Continual Policy Learning from Real-Time Human Feedback via Preference-Based Learning
AB-UPT: Scaling Neural CFD Surrogates for High- Fidelity Automotive Aerodynamics Simulations via Anc...
Teaching Diffusion Models to Ground Alpha Matte
Exponential Scaling of Factual Inconsistency in Data-to-Text Generation with Fine-Tuned LLMs
Data-Driven Discovery of PDEs via the Adjoint Method
Learning Reward Machines from Partially Observed Policies