4/20/2026
InfoChess: A Game of Adversarial Inference and a Laboratory for Quantifiable Information Control
Symmetric adversarial game framework for studying information acquisition and inference without material incentives or piece capture.
4/20/2026
Prompt-Driven Code Summarization: A Systematic Literature Review
Systematic literature review of LLM-based code summarization techniques for automatic software documentation generation using prompt engineering.
4/20/2026
(1D) Ordered Tokens Enable Efficient Test-Time Search
Study on ordered tokenization enabling efficient test-time search in autoregressive generative models through token structure optimization.
4/20/2026
Ragged Paged Attention: A High-Performance and Flexible LLM Inference Kernel for TPU
Optimized LLM inference kernel for TPU deployment with efficient paged attention mechanism handling dynamic ragged workloads.
4/20/2026
Lossless Compression via Chained Lightweight Neural Predictors with Information Inheritance
Lossless compression approach using chain of lightweight neural predictors for probability estimation in Markov sources.
4/20/2026
Why Fine-Tuning Encourages Hallucinations and How to Fix It
Study on how supervised fine-tuning increases LLM hallucinations through exposure to new facts and mitigation using continual learning techniques.
4/20/2026
Learning Behaviorally Grounded Item Embeddings via Personalized Temporal Contexts
Item embedding method for recommender systems that captures temporal dynamics of user preferences beyond bag-of-items approaches.
4/20/2026
"Excuse me, may I say something..." CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert Collaborations
Proactive AI assistant using LLMs for biomedical discovery, enabling autonomous engagement and foresight in human-AI collaboration workflows.
4/20/2026
LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance
Attribution analysis comparing interpretive behaviors of LLMs across fine-tuning strategies (FFT, LoRA) for code compliance tasks using perturbation methods.
4/20/2026
AdaVFM: Adaptive Vision Foundation Models for Edge Intelligence via LLM-Guided Execution
Adaptive framework for efficient edge deployment of language-aligned vision foundation models with dynamic computation adjustment based on scene context.
4/20/2026
SIMMER: Cross-Modal Food Image--Recipe Retrieval via MLLM-Based Embedding
Cross-modal retrieval system using multimodal LLM embeddings to match food images with recipe text for cooking and nutrition applications.
4/20/2026
The Metacognitive Monitoring Battery: A Cross-Domain Benchmark for LLM Self-Monitoring
Cross-domain benchmark for evaluating LLM self-monitoring and metacognitive abilities across 524 tasks in six cognitive domains using psychometric methodology.
4/20/2026
Structured Abductive-Deductive-Inductive Reasoning for LLMs via Algebraic Invariants
Symbolic reasoning scaffold operationalizing Peirce's abduction-deduction-induction framework with algebraic invariants to improve structured logical reasoning in LLMs.
4/20/2026
Breaking the Training Barrier of Billion-Parameter Universal Machine Learning Interatomic Potentials
Framework for training billion-parameter universal ML interatomic potentials without explosive memory growth, enabling quantum-accurate physical simulations.
4/20/2026
DiZiNER: Disagreement-guided Instruction Refinement via Pilot Annotation Simulation for Zero-shot Named Entity Recognition
DiZiNER: instruction refinement method using disagreement-guided pilot annotation simulation to improve zero-shot named entity recognition with LLMs.
4/20/2026
RAGognizer: Hallucination-Aware Fine-Tuning via Detection Head Integration
RAGognizer: detection head integration method for fine-tuning LLMs to reduce hallucinations and closed-domain inconsistencies in retrieval-augmented generation.
4/20/2026
Discovering quantum phenomena with Interpretable Machine Learning
Interpretable machine learning techniques for extracting physical insights from quantum data using variational autoencoders on unlabeled datasets.
4/20/2026
SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systems
SocialGrid benchmark for evaluating LLM agents on planning, task execution, and social reasoning in embodied multi-agent environments inspired by Among Us.
4/20/2026
Where does output diversity collapse in post-training?
Analysis of output diversity collapse in post-trained language models, showing models produce less varied outputs than base versions, affecting inference-time scaling.
4/20/2026
Cut Your Losses! Learning to Prune Paths Early for Efficient Parallel Reasoning
Systematic taxonomy and methods for pruning futile reasoning paths in Large Reasoning Models to improve efficiency and reduce inference costs.
4/20/2026
Towards Intrinsic Interpretability of Large Language Models:A Survey of Design Principles and Architectures
Survey of intrinsic interpretability design principles and architectures for LLMs, focusing on transparency built into models rather than post-hoc explanations.
4/20/2026
Constant-Factor Approximations for Doubly Constrained Fair k-Center, k-Median and k-Means
arXiv paper on constant-factor approximation algorithms for fair k-clustering with demographic constraints.
4/20/2026
Towards Universal Convergence of Backward Error in Linear System Solvers
arXiv paper on backward error analysis and convergence for linear system solvers in numerical linear algebra.
4/20/2026
Early Detection of Acute Myeloid Leukemia (AML) Using YOLOv12 Deep Learning Model
arXiv paper applying YOLOv12 deep learning model for multiclass acute myeloid leukemia cell classification.
4/20/2026
Stylistic-STORM (ST-STORM) : Perceiving the Semantic Nature of Appearance
arXiv paper on ST-STORM self-supervised learning approach for appearance-based image representation.
4/20/2026
Sentiment Analysis of German Sign Language Fairy Tales
arXiv paper on sentiment analysis dataset and LLM-based model for German sign language fairy tales.
4/20/2026
AtManRL: Towards Faithful Reasoning via Differentiable Attention Saliency
arXiv paper on AtManRL method using differentiable attention for faithful chain-of-thought reasoning in LLMs.
4/20/2026
Adaptive multi-fidelity optimization with fast learning rates
arXiv paper on adaptive multi-fidelity optimization with cost-bias tradeoffs and learning rate analysis.
4/20/2026
Information Router for Mitigating Modality Dominance in Vision-Language Models
arXiv paper on Information Router to mitigate modality dominance in vision-language models.
4/20/2026
Learning to Reason with Insight for Informal Theorem Proving
arXiv paper proposing framework for informal theorem proving with LLMs using insight-driven reasoning.
4/20/2026
Automatic Combination of Sample Selection Strategies for Few-Shot Learning
arXiv paper on ACSESS method for automatic combination of sample selection strategies in few-shot LLM learning.
4/20/2026
Heterogeneous Sheaf Neural Networks
arXiv paper proposing HetSheaf, a framework for heterogeneous graph neural networks across different node/edge types.
4/20/2026
Transformer Neural Processes - Kernel Regression
arXiv paper on HetSheaf framework for heterogeneous graph neural networks supporting multiple node/edge types in real-world applications.
4/20/2026
FSPO: Few-Shot Optimization of Synthetic Preferences Personalizes to Real Users
arXiv paper introducing Transformer Neural Processes addressing O(n²) attention bottleneck in Neural Processes with kernel regression.
4/20/2026
AutoNFS: Automatic Neural Feature Selection
arXiv paper on Few-Shot Preference Optimization (FSPO) for personalizing LLMs using meta-learning on synthetic preference data.
4/20/2026
Enhancing Visual Representation with Textual Semantics: Textual Semantics-Powered Prototypes for Heterogeneous Federated Learning
arXiv paper on AutoNFS, automatic neural feature selection for high-dimensional tabular data with interpretability and efficiency focus.
4/20/2026
Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State- Space Architectures from S4 to Mamba
arXiv paper on Federated Prototype Learning combining textual semantics with visual representations to handle heterogeneous federated learning.
4/20/2026
An Information-Geometric Approach to Artificial Curiosity
Information-geometric framework for artificial curiosity in sparse-reward RL using intrinsic rewards invariant to representation.
4/20/2026
A Tale of Two Learning Algorithms: Multiple Stream Random Walk and Asynchronous Gossip
Theoretical and empirical analysis of decentralized learning algorithms comparing multi-stream random walk and asynchronous gossip approaches.
4/20/2026
Histogram-based Parameter-efficient Tuning for Passive and Active Sonar Classification
Histogram-based parameter-efficient tuning (HPT) technique for transfer learning capturing target domain statistics in sonar classification.
4/20/2026
Softpick: No Attention Sink, No Massive Activations with Rectified Softmax
Softpick: Rectified softmax replacement for transformer attention eliminating attention sink and reducing activations with improved quantization.
4/20/2026
ChemAmp: Amplified Chemistry Tools via Composable Agents
ChemAmp: Framework for composable LLM agents in chemistry using tool amplification to enhance multi-tool orchestration capabilities.
4/20/2026
Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning
Token significance-aware RL method for LLM reasoning that optimizes token-level contributions rather than uniform length penalties.
4/20/2026
PyLO: Towards Accessible Learned Optimizers in PyTorch
PyLO: PyTorch package making learned optimizers accessible, providing drop-in replacements for standard optimizers like Adam.
4/20/2026
HiPreNets: High-Precision Neural Networks through Progressive Training
HiPreNets: Progressive training approach for neural networks achieving high precision in L-infinity norm error for safety-critical applications.
4/20/2026
Exploitation Over Exploration: Unmasking the Bias in Linear Bandit Recommender Offline Evaluation
Analysis of exploration-exploitation bias in offline evaluation of linear bandit recommender systems using contextual bandits.
4/20/2026
Self-Aligned Reward: Towards Effective and Efficient Reasoners
Self-aligned reward (SAR) method for LLM reasoning that provides fine-grained guidance beyond binary correctness to improve efficiency and accuracy.
4/20/2026
Online Distributionally Robust LLM Alignment via Regression to Relative Reward
Distributionally robust optimization approach for RLHF alignment addressing overoptimization in LLM training via relative reward regression.
4/20/2026
Bridging the phenotype-target gap for molecular generation via multi-objective reinforcement learning
SmilesGEN: VAE-based generative model using multi-objective RL for de novo drug molecule generation considering phenotypic effects.
4/20/2026
Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical Reasoning
Empirical study of scaling behaviors in RL post-training for LLMs across Qwen2.5 models (0.5B-72B) focused on mathematical reasoning performance.