Research
Curated daily papers, lab research blogs and national AI research programs across the US, China, EU, UK, Japan and beyond.
Curated daily papers, lab research blogs and national AI research programs across the US, China, EU, UK, Japan and beyond.
Latest in Research
30 storiesA Hybrid Framework For Crypto-Ransomware Detection In Enterprise Shared Storage
Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints. Consequently, ransom…
Wireless Backdoor Attack and Defense for Semantic Communications over Multiple Access Channel
Semantic communication (SemCom) aims to preserve semantic meaning and task-oriented information beyond conventional message recovery over wireless channels. The…
One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining
Modern large-scale LLM pretraining benefits from utilizing Pipeline Parallelism; however, synchronous implementations leave GPUs idle during pipeline bubbles, w…
Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity
AI agents can't remember past conversations. They must constantly reload or retrieve context, which grows less efficient as tasks get longer and more complex. M…
Import AI 463: Self-improving robots; a 10k Chinese GPU cluster; and an elegiac essay for the human era
What eras bookend our interregnum?…
Intent-Governed Tool Authorization for AI Agents
AI agents increasingly act through external tools: they read private data, construct structured payloads, submit write requests, export records, and coordinate …
Humanoid-OmniOcc: Stereo-Based Full-View Occupancy Dataset for Embodied AI
Occupancy prediction at voxel-level granularity is essential for safe robotic navigation and interaction in complex environments. Existing occupancy datasets, h…
Unlocking In-Context Learning in Audio-Language Models from Decentralized Medical Audio
Clinical audio diagnosis in low-resource settings requires models that identify conditions from minimal examples without large annotated corpora. We propose Fed…
On the Limits of Prompt-Conditioned Language Models as General-Purpose Learners
Large Language Models (LLMs) are frequently portrayed as general-purpose solvers capable of solving arbitrary tasks. We argue that this view overlooks a fundame…
ABACUS: Adapting Unified Foundation Model for Bridging Image Count Understanding and Generation
ABACUS is a unified vision-language model that handles object counting, crowd counting, referring-expression counting, and count-faithful image generation witho…
The Measurable Majority
This paper studies strict majority reasoning in finite electorates using so-called $\textit{social decision frames}$: finite sets of voters equipped with distin…
Digital Twin-Driven Adaptive Sim-to-Real Alignment via Reinforcement Learning for Vibration-Based Bearing Health Monitoring Under Data Scarcity
Vibration-based health monitoring of rotating machinery requires reliable fault diagnosis under operational data constraints, yet condition assessment remains c…
REDI-Match: Rotation-Equivariant Distillation for Efficient and Robust Dense Matching
Vision Foundation Models (VFMs) have significantly advanced dense feature matching, yet severe in-plane rotation remains a critical challenge. Existing solution…
Automatic Part-of-Speech Tagging of Arabic-English Dictionary Senses through WordNet
This paper proposed an algorithm for part-of-speech (POS) tagging senses of a bilingual dictionary. The algorithm is applied on the Al-Mawrid Arabic-English dic…
Solving Markov Decision Processes with Future Information via MPC
Model Predictive Control (MPC) is widely used in industrial and robotic systems for enforcing constraints and embedding domain knowledge through finite-horizon …
Paying to Know: Micro-Transaction Markets for Verified Product Information in Agentic E-Commerce
Commercial NLP treats the shopping chatbot as a recommender or a conversion tool: its job is to match a user to a catalogue entry and close a sale. We argue tha…
Scalable Peptide Design via Memory-Efficient Equivariant Transformer
Target-specific peptide design requires sequence and structure co-design under full atom geometric constraints. Latent generative frameworks offer an effective …
IV-CoT: Implicit Visual Chain-of-Thought for Structure-Aware Text-to-Image Generation
Unified multi-modal large language models (MLLMs) have achieved strong text-to-image generation quality, but still struggle with structure-aware prompt followin…
Benchmarking the Alignment of Data-Quality Metrics, Human Judgment and Land-Cover Segmentation Performance for Earth Observation
Volume and quality of datasets are crucial for deep learning model training, yet they are often constrained by availability and data acquisition costs. Syntheti…
The Gentle Collapse: Distributional Metrics for Continual Learning
Accuracy degradation is the standard metric for Catastrophic Forgetting (CF), however, it records only whether forgetting occurred or not. It saturates at the e…
Dual Agreement Consistency Learning for Semi-Supervised Fetal Ultrasound Segmentation
Maternal-fetal US is the primary imaging modality for monitoring fetal development, yet accurate automated segmentation remains challenging due to the scarcity …
Beyond Visual Forensics: Auditing Multimodal Robustness for Synthetic Medical Image Detection
With the rapid adoption of generative AI, synthetic medical images pose growing risks, including diagnostic deception and insurance fraud. Although prior work h…
Story Operators: Decomposing the Original $\to$ Sequel Transformation in Embedding Space
I treat a book as a point in a sentence-embedding space and a literary transformation as an operation on points. Given an original novel and its sequel, I ask w…
BrainAgent: A Large Language Model-Driven Multi-Agent Framework for Autonomous Brain Signal Understanding
Brain-Computer Interfaces (BCIs) and brain signal understanding are pivotal for clinical health and next-generation interactions. Despite this significance, its…
\chisao{}: A GPU-Native Parallel Optimizer for Multimodal Black-Box Functions via Convergence-Anticonvergence Oscillation
Finding all modes of a multimodal black-box function is a fundamental challenge in optimization, Bayesian inference, and scientific computing. Existing approach…
SidConArena: An Environment Evaluating Agents in Open-Ended,Positive-Sum Bargaining Game
Evaluating LLM agents requires dynamic environments that go beyond static reasoning and zero-sum games. Real-world economic interaction is often open-ended and …
SurgAtlas: A Large-Scale Surgical Video-Language Dataset with 2,391 Hours of Open and Minimally Invasive Surgery
We introduce SurgAtlas, the largest surgical video-language dataset to date, comprising 15,291 videos (2,391 hours) spanning 18 surgical specialties and over 5,…
Variable Bound Tightening for Nash Equilibrium Computation in Multiplayer Imperfect-Information Games
There has been significant recent progress in algorithms for approximation of Nash equilibrium in large two-player zero-sum imperfect-information games and exac…
Phonetic and semantic analyses of spoken corpora of Beijing and Taiwan Mandarin indicate that the neutral tone is a lexical tone
The neutral, or floating, tone of Mandarin Chinese is a tone with an enigmatic set of properties. It has been described as a reduced tone, or as a tone that som…
Geometry-Aware MCTS for Extremal Problems in Combinatorial Geometry
We study certain extremal problems in combinatorial geometry that ask about configurations of points in an $n \times n$ grid that satisfy strict, global geometr…