3/25/2026
Early Discoveries of Algorithmist I: Promise of Provable Algorithm Synthesis at Scale
Study on using LLMs for algorithm synthesis with provable guarantees, combining mathematical reasoning with practical performance.
3/25/2026
MCLR: Improving Conditional Modeling in Visual Generative Models via Inter-Class Likelihood-Ratio Maximization and Establishing the Equivalence between Classifier-Free Guidance and Alignment Objectives
Research on improving conditional modeling in diffusion models, establishing equivalence between classifier-free guidance and alignment objectives.
3/25/2026
Q-AGNN: Quantum-Enhanced Attentive Graph Neural Network for Intrusion Detection
Quantum-enhanced graph neural network for network intrusion detection exploiting relational dependencies in traffic flows.
3/25/2026
Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks
Quantum federated autoencoder framework for anomaly detection in IoT networks using quantum computing and federated learning.
3/25/2026
Reasoner-Executor-Synthesizer: Scalable Agentic Architecture with Static O(1) Context Window
Proposes Reasoner-Executor-Synthesizer architecture for LLM agents that maintains O(1) context window while avoiding hallucination and token cost scaling.
3/25/2026
When Visuals Aren't the Problem: Evaluating Vision-Language Models on Misleading Data Visualizations
Research evaluating Vision-Language Models' ability to detect misleading data visualizations and deceptive captions in charts.
3/25/2026
SynLeaF: A Dual-Stage Multimodal Fusion Framework for Synthetic Lethality Prediction Across Pan- and Single-Cancer Contexts
Multimodal fusion framework for synthetic lethality prediction in cancer drug development addressing modality laziness problem.
3/25/2026
FAAR: Format-Aware Adaptive Rounding for NVFP4
FAAR quantization method for NVFP4 ultra-low-bit format that adapts rounding to non-uniform numerical grid for efficient LLM edge deployment.
3/25/2026
Rethinking Multimodal Fusion for Time Series: Auxiliary Modalities Need Constrained Fusion
Study on multimodal fusion strategies for time series forecasting showing naive fusion fails and proposing constrained fusion approach.
3/25/2026
Three Creates All: You Only Sample 3 Steps
MTEO method for few-step diffusion sampling by distilling layer-wise, step-wise time embeddings to accelerate inference.
3/25/2026
AI Co-Scientist for Ranking: Discovering Novel Search Ranking Models alongside LLM-based AI Agents with Cloud Computing Access
AI Co-Scientist framework combining LLM agents with cloud computing to automate search ranking research from ideation through GPU training.
3/25/2026
Abnormalities and Disease Detection in Gastro-Intestinal Tract Images
PhD thesis on classification and segmentation of gastrointestinal tract images for real-time medical diagnosis applications.
3/25/2026
Instruction-Tuned, but Not More Verifiable Instruction-Following: A Cross-Task Diagnosis for LoRA Adapters
Cross-task evaluation study of LoRA adapters showing nominal instruction-tuning labels don't reliably predict realized instruction-following capabilities.
3/25/2026
Symbolic Graph Networks for Robust PDE Discovery from Noisy Sparse Data
Symbolic Graph Network framework for discovering partial differential equations from noisy sparse data without numerical differentiation.
3/25/2026
Learning When to Act: Interval-Aware Reinforcement Learning with Predictive Temporal Structure
Adaptive temporal control system for autonomous agents that learns optimal action intervals using hyperbolic geometry predictive signals.
3/25/2026
Latent Style-based Quantum Wasserstein GAN for Drug Design
Quantum Wasserstein GAN with latent style representation for de novo drug design using generative AI.
3/25/2026
CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation
Open-source framework (CaP-X) for benchmarking and improving code-as-policy agents for robot manipulation tasks.
3/25/2026
Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs
Token-level analysis of distributional shifts in RLVR fine-tuning of LLMs to understand mechanisms underlying reasoning improvements.
3/25/2026
LLM-guided headline rewriting for clickability enhancement without clickbait
LLM-guided headline rewriting system that enhances reader engagement while maintaining editorial integrity and avoiding clickbait.
3/25/2026
Color When It Counts: Grayscale-Guided Online Triggering for Always-On Streaming Video Sensing
Edge AI video sensing paradigm using grayscale capture with selective RGB frames to reduce bandwidth and computational requirements.
3/25/2026
Stability-Preserving Online Adaptation of Neural Closed-loop Maps
Online adaptation method for neural closed-loop control systems that preserves stability while updating controllers during operation.
3/25/2026
Functional Component Ablation Reveals Specialization Patterns in Hybrid Language Model Architectures
Ablation study analyzing specialization patterns in hybrid language models combining attention with state space models on sub-1B parameter models.
3/25/2026
Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Games
Framework for building language model general capabilities via automatic curriculum of cross-entropy game tasks for relevant skill discovery.
3/25/2026
Tiny Inference-Time Scaling with Latent Verifiers
Inference-time scaling method using small latent verifiers instead of multimodal LLMs to score and select outputs while reducing computational cost.
3/25/2026
Do Large Language Models Reduce Research Novelty? Evidence from Information Systems Journals
Empirical study measuring semantic novelty of 13,847 IS papers (2020-2025) to assess whether LLM productivity gains translate to genuine intellectual advancement.
3/25/2026
High Resolution Flood Extent Detection Using Deep Learning with Random Forest Derived Training Labels
Deep learning framework for flood detection using satellite imagery and random forest-derived labels to map flood extent during disasters.
3/25/2026
LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface
LLMON proposes a markup language for LLMs that preserves structure and semantics in prompts, distinguishing between instructions and data in input/output.
3/25/2026
GraphRAG for Engineering Diagrams: ChatP&ID Enables LLM Interaction with P&IDs
ChatP&ID is an agentic RAG framework enabling LLM interaction with engineering P&ID diagrams using knowledge graphs for cost-effective grounded reasoning.
3/25/2026
Ego2Web: A Web Agent Benchmark Grounded in Egocentric Videos
Ego2Web benchmark for multimodal web agents grounded in egocentric video, evaluating agents performing real-world workflows with physical context awareness.
3/25/2026
STRIATUM-CTF: A Protocol-Driven Agentic Framework for General-Purpose CTF Solving
STRIATUM-CTF is an agentic framework using search-based reasoning for automated cybersecurity CTF challenge solving with multi-step stateful reasoning.
3/25/2026
Lie to Me: How Faithful Is Chain-of-Thought Reasoning in Reasoning Models?
Study evaluating faithfulness of chain-of-thought reasoning in LLMs, finding models often produce misleading explanations despite correct outputs.
3/25/2026
flexvec: SQL Vector Retrieval with Programmatic Embedding Modulation
flexvec is a SQL vector retrieval kernel exposing embedding matrices and score arrays for programmatic manipulation by AI agents via Programmatic Embedding Modulation.
3/25/2026
Language Models Can Explain Visual Features via Steering
Method leveraging vision-language models to explain sparse autoencoder features in vision models through causal interventions instead of correlation-based approaches.
3/25/2026
Do Consumers Accept AIs as Moral Compliance Agents?
Survey studying consumer acceptance of AI in moral compliance roles versus moral decision-making across five studies.
3/25/2026
Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions
Theoretical work on causal discovery in chain-reaction systems using interventional data, proving identifiability under cascade-like structural assumptions.
3/25/2026
To Agree or To Be Right? The Grounding-Sycophancy Tradeoff in Medical Vision-Language Models
Evaluation of medical vision-language models revealing a grounding-sycophancy tradeoff, analyzing hallucination and agreement behaviors across six VLMs.
3/25/2026
Toward Faithful Segmentation Attribution via Benchmarking and Dual-Evidence Fusion
Benchmark for evaluating attribution map faithfulness in semantic segmentation models, testing intervention-based faithfulness and perturbation robustness.
3/25/2026
LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation
LGSE framework for adapting pretrained language models to low-resource languages using morphologically grounded subword embeddings instead of arbitrary segmentation.
3/25/2026
Learning to Trust: How Humans Mentally Recalibrate AI Confidence Signals
Study examining whether humans can learn to recalibrate AI confidence signals through repeated interaction, testing four calibration conditions with 200 participants.
3/25/2026
AwesomeLit: Towards Hypothesis Generation with Agent-Supported Literature Research
AwesomeLit proposes an agent-supported literature research system for hypothesis generation, designed for inexperienced researchers to identify gaps and propose feasible research directions.
3/25/2026
Generalizing Dynamics Modeling More Easily from Representation Perspective
Neural dynamics modeling approach from representation perspective for system behavior learning.
3/25/2026
Vision-based Deep Learning Analysis of Unordered Biomedical Tabular Datasets via Optimal Spatial Cartography
Vision-based deep learning method for unordered biomedical tabular data via optimal spatial cartography.
3/25/2026
WiFi2Cap: Semantic Action Captioning from Wi-Fi CSI via Limb-Level Semantic Alignment
Wi-Fi CSI-based system for privacy-preserving semantic action captioning using limb-level alignment.
3/25/2026
PopResume: Causal Fairness Evaluation of LLM/VLM Resume Screeners with Population-Representative Dataset
Population-representative resume dataset for causal fairness auditing of LLM/VLM-based screening systems.
3/25/2026
KALAVAI: Predicting When Independent Specialist Fusion Works -- A Quantitative Model for Post-Hoc Cooperative LLM Training
Quantitative model predicting when post-hoc fusion of independent LLM specialists outperforms individual models.
3/25/2026
DALDALL: Data Augmentation for Lexical and Semantic Diverse in Legal Domain by leveraging LLM-Persona
Persona-based data augmentation framework using LLMs for legal domain information retrieval in low-resource settings.
3/25/2026
From Overload to Convergence: Supporting Multi-Issue Human-AI Negotiation with Bayesian Visualization
Bayesian visualization interface supporting multi-issue human-AI negotiation to manage cognitive load.
3/25/2026
From Arithmetic to Logic: The Resilience of Logic and Lookup-Based Neural Networks Under Parameter Bit-Flips
Study of neural network resilience to hardware bit-flip errors, comparing logic-based vs arithmetic architectures.
3/25/2026
KARMA: Knowledge-Action Regularized Multimodal Alignment for Personalized Search at Taobao
LLM fine-tuning framework addressing knowledge-action gap in personalized e-commerce search at Taobao.
3/25/2026
Exposure-Normalized Bed and Chair Fall Rates via Continuous AI Monitoring
Hospital study measuring fall rates using continuous AI monitoring systems from August 2024 to December 2025.