3/13/2026
MedEyes: Learning Dynamic Visual Focus for Medical Progressive Diagnosis
MedEyes applies vision-language models with reinforcement learning for medical diagnosis via dynamic visual focusing and iterative clinical reasoning.
3/13/2026
Knowledge Distillation with Structured Chain-of-Thought for Text-to-SQL
Knowledge distillation method using structured chain-of-thought to improve text-to-SQL performance in small language models while reducing cost and security risks.
3/13/2026
KnowVal: A Knowledge-Augmented and Value-Guided Autonomous Driving System
KnowVal combines visual-language reasoning, driving knowledge, and value alignment for autonomous driving using knowledge-augmented approaches beyond data-driven learning.
3/13/2026
Do LLMs Judge Distantly Supervised Named Entity Labels Well? Constructing the JudgeWEL Dataset
Dataset (judgeWEL) for named entity recognition in Luxembourgish using LLMs to verify automatically labeled data for underrepresented languages.
3/13/2026
LLMTrack: Semantic Multi-Object Tracking with Multi-modal Large Language Models
Benchmark and framework (Grand-SMOT) for semantic multi-object tracking using multimodal LLMs to handle complex relational queries.
3/13/2026
LLM-driven Multimodal Recommendation
arXiv: LMMRec framework using LLMs to model user motivations in multimodal recommendation systems from heterogeneous information sources.
3/13/2026
LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
arXiv: LatentChem decouples chemical reasoning from natural language by using latent representations instead of chain-of-thought prompting.
3/13/2026
Controllable Exploration in Hybrid-Policy RLVR for Multi-Modal Reasoning
arXiv: Hybrid-policy reinforcement learning approach for enhancing multi-modal LLM reasoning with controlled exploration strategies.
3/13/2026
Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction
arXiv: Evaluating small language models for zero-shot and one-shot role classification in robot leader-follower interaction tasks.
3/13/2026
FlashOptim: Optimizers for Memory-Efficient Training
arXiv: FlashOptim memory-efficient optimizers for mixed-precision neural network training reducing parameter storage overhead.
3/13/2026
ProtoDCS: Towards Robust and Efficient Open-Set Test-Time Adaptation for Vision-Language Models
arXiv: ProtoDCS framework for robust test-time adaptation of Vision-Language Models under distribution shift and open-set scenarios.
3/13/2026
Can LLM Aid in Solving Constraints with Inductive Definitions?
arXiv: Using LLMs with structured prompts to generate auxiliary lemmas for constraint solving with inductive definitions.
3/13/2026
Understanding Parents' Desires in Moderating Children's Interactions with GenAI Chatbots through LLM-Generated Probes
Study of parental moderation preferences for children's GenAI chatbot interactions using LLM-generated probe scenarios.
3/13/2026
BLOCK: An Open-Source Bi-Stage MLLM Character-to-Skin Pipeline for Minecraft
BLOCK: open-source two-stage MLLM pipeline generating Minecraft character skins from text descriptions via 3D preview synthesis.
3/13/2026
Benchmark of Benchmarks: Unpacking Influence and Code Repository Quality in LLM Safety Benchmarks
Multi-dimensional evaluation of LLM safety benchmarks assessing their academic influence and code repository quality.
3/13/2026
Reasoning Theater: Disentangling Model Beliefs from Chain-of-Thought
Analysis of performative chain-of-thought in reasoning LLMs showing discrepancy between generated explanations and internal model beliefs.
3/13/2026
From Toil to Thought: Designing for Strategic Exploration and Responsible AI in Systematic Literature Reviews
Design study on LLM-assisted tools for systematic literature reviews to reduce cognitive load and enable iterative exploration.
3/13/2026
On the Value of Tokeniser Pretraining in Physics Foundation Models
Investigation of tokenizer pretraining impact on physics foundation models for emulating complex multiphysics simulations.
3/13/2026
Computational Pathology in the Era of Emerging Foundation and Agentic AI -- International Expert Perspectives on Clinical Integration and Translational Readiness
Expert perspectives on integrating foundation models and AI agents into clinical computational pathology with translational readiness assessment.
3/13/2026
Evaluating LLM-Based Grant Proposal Review via Structured Perturbations
Framework using structured perturbations to evaluate LLM performance on high-stakes grant proposal reviews across quality dimensions.
3/13/2026
EXPLORE-Bench: Egocentric Scene Prediction with Long-Horizon Reasoning
EXPLORE-Bench benchmark evaluating multimodal LLMs' ability to reason about long-horizon physical consequences from egocentric viewpoints.
3/13/2026
AraModernBERT: Transtokenized Initialization and Long-Context Encoder Modeling for Arabic
AraModernBERT adapter for Arabic NLP with transtokenized embeddings and 8K token context window support.
3/13/2026
Leveraging Wikidata for Geographically Informed Sociocultural Bias Dataset Creation: Application to Latin America
Dataset creation using Wikidata to detect cultural biases in LLMs across Latin American languages and contexts.
3/13/2026
SENS-ASR: Semantic Embedding injection in Neural-transducer for Streaming Automatic Speech Recognition
Semantic embedding injection in neural transducers for low-latency streaming automatic speech recognition.
3/13/2026
The Epistemic Support-Point Filter: Jaynesian Maximum Entropy Meets Popperian Falsification
Epistemic Support-Point Filter for recursive estimation using maximum entropy and falsification principles.
3/13/2026
Rethinking the Harmonic Loss via Non-Euclidean Distance Layers
Proposes harmonic loss as alternative to cross-entropy for training deep neural networks with improved interpretability.
3/13/2026
Contract And Conquer: How to Provably Compute Adversarial Examples for a Black-Box Model?
Method to provably compute adversarial examples for black-box neural networks using Contract And Conquer approach.
3/13/2026
Towards Robust Speech Deepfake Detection via Human-Inspired Reasoning
Human-inspired reasoning approach for robust speech deepfake detection with improved generalization to unseen audio domains and interpretability.
3/13/2026
On the Reliability of Cue Conflict and Beyond
Analysis of cue-conflict benchmarks for measuring neural network shape-texture bias, identifying instability in stylization-based bias estimation methods.
3/13/2026
Historical Consensus: Preventing Posterior Collapse via Iterative Selection of Gaussian Mixture Priors
Historical Consensus approach for preventing posterior collapse in VAEs through iterative Gaussian mixture prior selection based on data covariance spectral properties.
3/13/2026
Structure-Aware Epistemic Uncertainty Quantification for Neural Operator PDE Surrogates
Uncertainty quantification framework for neural operator PDE surrogates emphasizing computational efficiency and spatial localization of epistemic uncertainty.
3/13/2026
Interventional Time Series Priors for Causal Foundation Models
Interventional time series data generator for training causal foundation models, extending prior-data fitted networks to time series with ground-truth interventions.
3/13/2026
Graph Tokenization for Bridging Graphs and Transformers
Graph tokenization framework combining reversible serialization with BPE to enable transformer models to process graph-structured data as token sequences.
3/13/2026
Task-Conditioned Routing Signatures in Sparse Mixture-of-Experts Transformers
Analysis of routing signatures in sparse Mixture-of-Experts transformers to understand task-conditioned expert selection patterns in large language models.
3/13/2026
Learning Tree-Based Models with Gradient Descent
Gradient descent-based approach for learning interpretable tree-based decision models, addressing combinatorial complexity of traditional discrete tree learning.
3/13/2026
A Learning-Based Superposition Operator for Non-Renewal Arrival Processes in Queueing Networks
Data-driven superposition operator for non-renewal arrival processes in queueing networks using moment-based learning instead of classical analytical methods.
3/13/2026
High-resolution weather-guided surrogate modeling for data-efficient cross-location building energy prediction
Surrogate modeling approach for building energy prediction using weather-guided models to reduce computational cost of physics-based EnergyPlus simulations.
3/13/2026
Higher-Order Modular Attention: Fusing Pairwise and Triadic Interactions for Protein Sequences
Higher-Order Modular Attention (HOMA) mechanism extending transformer attention to capture triadic interactions in protein sequences beyond pairwise dependencies.
3/13/2026
Scaling Reasoning Efficiently via Relaxed On-Policy Distillation
REOPOLD: framework for on-policy distillation of reasoning capabilities to smaller models using policy optimization and token-level rewards for efficient scaling.
3/13/2026
H2LooP Spark Preview: Continual Pretraining of Large Language Models for Low-Level Embedded Systems Code
H2LooP Spark Preview: continual pretraining framework for LLMs specialized in low-level embedded systems code generation with hardware-specific domain adaptation.
3/13/2026
Attention Gathers, MLPs Compose: A Causal Analysis of an Action-Outcome Circuit in VideoViT
Mechanistic interpretability analysis of video vision transformers to understand how internal circuits represent action-outcome relationships in classification tasks.
3/13/2026
Systematic Scaling Analysis of Jailbreak Attacks in Large Language Models
Scaling-law framework for jailbreak attacks on LLMs treating each attack as compute-bounded optimization across methods and model families.
3/13/2026
Algorithmic Capture, Computational Complexity, and Inductive Bias of Infinite Transformers
Formal analysis of algorithmic learning (grokking) in infinite-width transformers with computational complexity bounds and generalization theory.
3/13/2026
Bayesian Optimization of Partially Known Systems using Hybrid Models
Bayesian optimization method combining probabilistic models with hybrid systems for efficient black-box optimization of expensive functions.
3/13/2026
Representation Finetuning for Continual Learning
Parameter-efficient fine-tuning approach for continual learning that controls representation-level adaptation in pretrained models.
3/13/2026
Reference-Guided Machine Unlearning
Machine unlearning method using reference-guided approach to remove data influence from trained models while preserving utility.
3/13/2026
Client-Conditional Federated Learning via Local Training Data Statistics
Federated learning method conditioning global model on client-specific PCA statistics for heterogeneous data without extra communication.
3/13/2026
Hindsight-Anchored Policy Optimization: Turning Failure into Feedback in Sparse Reward Settings
Hindsight-Anchored Policy Optimization for sparse-reward RL in reasoning model post-training, addressing advantage collapse.
3/13/2026
Meta-Reinforcement Learning with Self-Reflection for Agentic Search
MR-Search: meta-reinforcement learning framework for agentic search with self-reflection, enabling agents to improve in-context exploration.
3/13/2026
Jailbreak Scaling Laws for Large Language Models: Polynomial-Exponential Crossover
Analysis of adversarial attacks on LLMs showing polynomial-exponential crossover in success rates with inference-time samples.