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GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning

- Competitive programming remains one of the last few human strongholds in coding against AI. The best AI system to date still underperforms the best humans competitive programming: the most recent...

From Guessing to Seeing: Enhancing LLM-Based Program Repair via Trace-Guided Multi-strategy Debate

- Automated Program Repair (APR) aims to resolve software bugs without human intervention, but complex logic errors and silent failures remain challenging. Existing LLM-based APR methods mainly rely on...

TRU: Targeted Reverse Update for Efficient Multimodal Recommendation Unlearning

- Multimodal recommendation systems (MRS) jointly model user-item interaction graphs and rich item content, but this tight coupling makes user data difficult to remove once learned. Approximate machine...

Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning

- While test-time scaling has enabled large language models to solve highly difficult tasks, state-of-the-art results come at exorbitant compute costs. These inefficiencies can be attributed to the...

SimMOF: AI agent for Automated MOF Simulations

- Metal-organic frameworks (MOFs) offer a vast design space, and as such, computational simulations play a critical role in predicting their structural and physicochemical properties. However, MOF...

Gender-Based Heterogeneity in Youth Privacy-Protective Behavior for Smart Voice Assistants: Evidence from Multigroup PLS-SEM

- This paper investigates how gender shapes privacy decision-making in youth smart voice assistant (SVA) ecosystems. Using survey data from 469 Canadian youths aged 16-24, we apply multigroup Partial...

DFM-VLA: Iterative Action Refinement for Robot Manipulation via Discrete Flow Matching

- Vision-Language-Action (VLA) models that encode actions using a discrete tokenization scheme have been widely adopted for robotic manipulation, but existing decoding paradigms remain fundamentally...

A Benchmark for Evaluating Repository-Level Code Agents with Intermediate Reasoning on Feature Addition Task

- Repository-level code agents have shown strong promise in real-world feature addition tasks, making reliable evaluation of their capabilities increasingly important. However, existing benchmarks...

Query-Specific Pruning of RML Mappings (Extended Version)

- Current approaches for knowledge graph construction with RML focus on full RDF graph materialization without considering user queries, which is inefficient in dynamic query environments where often...

MMaDA-VLA: Large Diffusion Vision-Language-Action Model with Unified Multi-Modal Instruction and Generation

- Vision-Language-Action (VLA) models map visual observations and natural-language instructions to robot actions; however, hierarchical and autoregressive paradigms often incur architectural overhead,...

IPV-Bench: Benchmarking Image Protection Methods under Diverse Image-to-Video Generation Scenarios

- Image-to-video (I2V) generation models can be misused to animate a single image into a convincing fake video, motivating perturbation-based image protection methods that aim to disrupt such...

Communication-Aware Multi-Agent Reinforcement Learning for Decentralized Cooperative UAV Deployment

- Autonomous Unmanned Aerial Vehicle (UAV) swarms are increasingly used as rapidly deployable aerial relays and sensing platforms, yet practical deployments must operate under partial observability and...

Clinician input steers AI toward accurate and harmful recommendations

- Large language models (LLMs) are entering clinical workflows, yet evaluations rarely assess how clinician reasoning shapes model behavior during clinical interactions. Using 61 curated NEJM Case...

Switching-Reference Voltage Control for Distribution Systems with AI-Training Data Centers

- Large-scale AI training workloads in data centers exhibit rapid and periodic power swings that can induce voltage deviations in power distribution systems. Existing voltage controllers treat these...

Parallel-in-Time Nonlinear Optimal Control via GPU-native Sequential Convex Programming

- Real-time solution of nonlinear optimal control problems remains challenging on embedded robotic hardware, where conventional solvers often rely on global sparse linear algebra or sequential...

When Drafts Evolve: Speculative Decoding Meets Online Learning

- Speculative decoding has emerged as a widely adopted paradigm for accelerating large language model inference, where a lightweight draft model rapidly generates candidate tokens that are then...

OBASE: Object-Based Address-Space Engineering to Improve Memory Tiering

- Hardware and OS mechanisms for memory tiering are widely deployed, yet datacenters still overprovision DRAM. The root cause is hotness fragmentation: allocators place objects by size rather than...

MM-ISTS: Cooperating Irregularly Sampled Time Series Forecasting with Multimodal Vision-Text LLMs

- Irregularly sampled time series (ISTS) are widespread in real-world scenarios, exhibiting asynchronous observations on uneven time intervals across diverse variables. Existing ISTS forecasting...

Stochastic Parrots or Singing in Harmony? Testing Five Leading LLMs for their Ability to Replicate a Human Survey with Synthetic Data

- How well can AI-derived synthetic research data replicate the responses of human participants? An emerging literature has begun to engage with this question, which carries deep implications for...

Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing

- In many economically relevant contexts where machine learning is deployed, multiple platforms obtain data from the same pool of users, each of whom selects the platform that best serves them. Prior...

When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation

- Artificial intelligence benchmarks are an important mechanism to measure model progress and guide deployment decisions. However, benchmarks quickly "saturate", making it difficult to...