2/13/2026
EM-Aware Physical Synthesis: Neural Inductor Modeling and Intelligent Placement & Routing for RF Circuits
ML framework for RF circuit physical synthesis using neural inductor models and intelligent routing to generate GDSII layouts.
2/13/2026
Calibration and Evaluation of Car-Following Models for Autonomous Shuttles Using a Novel Multi-Criteria Framework
ML techniques applied to autonomous shuttle car-following models calibrated with field data. Peripheral to core interests.
2/13/2026
Budget-Constrained Agentic Large Language Models: Intention-Based Planning for Costly Tool Use
Research on budget-constrained LLM agents that plan tool use under monetary constraints. Addresses sequential decision-making with expensive tool executions.
2/13/2026
HyperDet: 3D Object Detection with Hyper 4D Radar Point Clouds
3D object detection framework using 4D mmWave radar point clouds with task-aware construction for improved weather-robust detection.
2/13/2026
The Five Ws of Multi-Agent Communication: Who Talks to Whom, When, What, and Why -- A Survey from MARL to Emergent Language and LLMs
Survey covering multi-agent communication mechanisms in MARL, emergent language, and LLM-based agents across autonomous and collaborative systems.
2/13/2026
PLESS: Pseudo-Label Enhancement with Spreading Scribbles for Weakly Supervised Segmentation
Weakly supervised segmentation method improving pseudo-label quality for scribble-based medical image annotations.
2/13/2026
Enforcing Reciprocity in Operator Learning for Seismic Wave Propagation
Neural operator incorporating physical reciprocity constraints for seismic wave propagation modeling and computational efficiency.
2/13/2026
Provable Offline Reinforcement Learning for Structured Cyclic MDPs
Offline reinforcement learning framework for cyclic MDPs with heterogeneous stage dynamics addressing state distribution mismatch.
2/13/2026
ThinkRouter: Efficient Reasoning via Routing Thinking between Latent and Discrete Spaces
Approach routing LLM reasoning between latent and discrete spaces to improve efficiency while maintaining reasoning quality and confidence.
2/13/2026
LAER-MoE: Load-Adaptive Expert Re-layout for Efficient Mixture-of-Experts Training
Training optimization technique for Mixture-of-Experts models addressing expert load imbalance through dynamic expert relayering.
2/13/2026
Estimation of instrument and noise parameters for inverse problem based on prior diffusion model
Bayesian approach for estimating observation parameters in inverse problems using diffusion priors for posterior sampling.
2/13/2026
Cross-Architecture Model Diffing with Crosscoders: Unsupervised Discovery of Differences Between LLMs
Method using crosscoders for comparing internal representations across different LLM architectures to identify safety-critical behavioral differences.
2/13/2026
Aggregate Models, Not Explanations: Improving Feature Importance Estimation
Framework for improving feature importance estimation stability by aggregating model explanations across ensemble members for scientific discovery.
2/13/2026
MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling
9B-parameter LLM architecture combining sparse and linear attention mechanisms for efficient long-context processing and reduced computational costs.
2/13/2026
TSR: Trajectory-Search Rollouts for Multi-Turn RL of LLM Agents
Training method for multi-turn RL of LLM agents using trajectory search rollouts to improve exploration in sparse reward environments.
2/13/2026
Decentralized Non-convex Stochastic Optimization with Heterogeneous Variance
Decentralized optimization algorithm for distributed machine learning addressing heterogeneous gradient variance across nodes.
2/13/2026
How to Sample High Quality 3D Fractals for Action Recognition Pre-Training?
Synthetic dataset generation using fractals for action recognition pre-training via Formula Driven Supervised Learning approach.
2/13/2026
A Comparative Study of MAP and LMMSE Estimators for Blind Inverse Problems
Comparative analysis of MAP and LMMSE estimators for blind inverse problems addressing non-convexity and solution non-identifiability.
2/13/2026
Revis: Sparse Latent Steering to Mitigate Object Hallucination in Large Vision-Language Models
Training-free framework using sparse latent steering to reduce object hallucination in large vision-language models via latent space geometry.
2/13/2026
EqDeepRx: Learning a Scalable MIMO Receiver
Deep learning approach for MIMO receiver design combining linear signal processing with ML blocks for improved scalability and explainability.
2/13/2026
Improving Neural Retrieval with Attribution-Guided Query Rewriting
Method using token-level explanations to guide LLM-based query rewriting for improving neural retrieval system robustness.
2/13/2026
Free Lunch for Stabilizing Rectified Flow Inversion
Research on stabilizing Rectified Flow generative models for improved inversion and downstream tasks like reconstruction and editing.
2/13/2026
Prototype Transformer: Towards Language Model Architectures Interpretable by Design
Prototype Transformer architecture designed for interpretability by design, enabling explicit and transparent reasoning in autoregressive language models.
2/13/2026
Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception
Region-to-Image Distillation approach for improving fine-grained visual understanding in MLLMs without repeated zooming during inference.
2/13/2026
DMAP: A Distribution Map for Text
DMAP method for analyzing text using LLM next-token probability distributions, improving on perplexity metrics for context-dependent interpretation.
2/13/2026
When Should LLMs Be Less Specific? Selective Abstraction for Reliable Long-Form Text Generation
Selective Abstraction framework for LLMs to improve factual reliability in long-form generation by abstaining when confidence is low rather than discarding information.
2/13/2026
Echo: Towards Advanced Audio Comprehension via Audio-Interleaved Reasoning
Large Audio Language Models framework using audio-interleaved reasoning to improve comprehension of complex audio content beyond one-time encoding.
2/13/2026
TADA! Tuning Audio Diffusion Models through Activation Steering
Research on activation steering in audio diffusion models to understand how semantic concepts are represented in attention layers.
2/13/2026
Benchmarking Vision-Language Models for French PDF-to-Markdown Conversion
Benchmark evaluating vision-language models for PDF-to-Markdown conversion on French documents. LLM application for document processing and RAG pipelines.
2/13/2026
Calibrated Bayesian Deep Learning for Explainable Decision Support Systems Based on Medical Imaging
Bayesian deep learning approach for calibrated uncertainty in medical imaging decision support. ML application, limited to healthcare domain.
2/13/2026
The Implicit Bias of Logit Regularization
Analysis of implicit bias from logit regularization in linear classifiers. Theoretical ML research, limited practical developer relevance.
2/13/2026
Safety Beyond the Training Data: Robust Out-of-Distribution MPC via Conformalized System Level Synthesis
Robust control framework combining conformal prediction and system level synthesis for learned dynamics models. Control theory, limited AI/ML interest.
2/13/2026
Towards Personalized Bangla Book Recommendation: A Large-Scale Multi-Entity Book Graph Dataset
Large-scale book graph dataset for personalized recommendation in Bangla. NLP dataset, but low relevance to core AI/ML development interests.
2/13/2026
STAR : Bridging Statistical and Agentic Reasoning for Large Model Performance Prediction
Framework combining statistical and agentic reasoning for predicting large model performance from limited data. AI agents for model evaluation.
2/13/2026
GPT-4o Lacks Core Features of Theory of Mind
Evaluation framework testing whether GPT-4o possesses theory of mind via causal mental state models. LLM capability research and evaluation.
2/13/2026
Convex Markov Games and Beyond: New Proof of Existence, Characterization and Learning Algorithms for Nash Equilibria
Theoretical analysis of Nash equilibria in convex Markov games and learning algorithms. Game theory foundations, limited practical AI application.
2/13/2026
Moonshine v2: Ergodic Streaming Encoder ASR for Latency-Critical Speech Applications
Low-latency speech recognition encoder for edge devices with streaming capability. Developer tool for real-time ASR applications.
2/13/2026
Is Online Linear Optimization Sufficient for Strategic Robustness?
Game theory analysis of bidding algorithms in repeated first-price auctions. Economics/game theory, not AI/ML development.
2/13/2026
Think like a Scientist: Physics-guided LLM Agent for Equation Discovery
Physics-guided LLM agent for symbolic equation discovery using multi-step reasoning. AI agents for scientific research with domain knowledge.
2/13/2026
T3D: Few-Step Diffusion Language Models via Trajectory Self-Distillation with Direct Discriminative Optimization
Few-step diffusion language model via trajectory self-distillation for faster parallel token decoding. LLM optimization for inference efficiency.
2/13/2026
MonarchRT: Efficient Attention for Real-Time Video Generation
Efficient attention mechanism for real-time video generation using diffusion transformers. Developer tool for reducing computational bottlenecks.
2/13/2026
Learning to Control: The iUzawa-Net for Nonsmooth Optimal Control of Linear PDEs
Neural network approach for solving nonsmooth optimal control of linear PDEs. Scientific computing, not directly ML/AI development.
2/13/2026
UniT: Unified Multimodal Chain-of-Thought Test-time Scaling
Unified multimodal model with test-time scaling via chain-of-thought reasoning for complex tasks. LLM application combining vision and language.
2/13/2026
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition
Algorithm for nuclear-norm regularized matrix optimization using Burer-Monteiro decomposition. Pure mathematics/optimization, no AI connection.
2/13/2026
Optimizing Sampling Patterns for Compressed Sensing MRI with Diffusion Generative Models
Diffusion models for accelerating MRI reconstruction by optimizing sampling patterns. Medical imaging application, not AI/ML development focused.
2/13/2026
Learning a Neural Solver for Parametric PDE to Enhance Physics-Informed Methods
Neural network approach to solve parametric partial differential equations and enhance physics-informed deep learning methods.
2/13/2026
Shallow Diffuse: Robust and Invisible Watermarking through Low-Dimensional Subspaces in Diffusion Models
Watermarking technique for embedding invisible watermarks in diffusion model outputs to prevent misuse of AI-generated images.
2/13/2026
PBP: Post-training Backdoor Purification for Malware Classifiers
Defense technique against backdoor poisoning attacks on machine learning malware classifiers through post-training purification.
2/13/2026
Compositional Generalization from Learned Skills via CoT Training: A Theoretical and Structural Analysis for Reasoning
Research on how Chain-of-Thought training enables LLMs to generalize by composing learned skills for complex reasoning tasks.
2/13/2026
Efficient and Sharp Off-Policy Learning under Unobserved Confounding
Off-policy learning method for personalized policies under unobserved confounding without unconfoundedness assumptions.