All entries

BranchIP: Learning Adaptive Equivariant Computation for Interatomic Potentials

arXiv:2610.02013v1 Announce Type: new Abstract: Equivariant machine learning interatomic potentials (MLIPs) have revolutionized atomistic modeling, but accurate treatment of complex materials and mole

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Bridging the Sim-to-Real Gap with multipanda_ros2: A Real-Time ROS2 Framework for Multimanual Systems

DGX agent

arXiv:2602.02269v2 Announce Type: replace-cross Abstract: We present multipanda_ros2, a novel open-source ROS2 architecture for multi-robot control of Franka Robotics robots. Leveraging ros2 control,

model-releasesarxiv-cs-ai

2 Oct 2026

BudgetSchemaBench: A Budget-Swept Diagnostic for Schema Context in Text-to-SQL

arXiv:2610.00092v1 Announce Type: cross Abstract: Data agents over structured sources must fit database schema into the model's context window. Large catalogs can span many databases and thousands of

Build2SPARQL: A Large-Scale Text-to-SPARQL Benchmark Dataset for Building Knowledge Graph Querying

arXiv:2610.00224v1 Announce Type: new Abstract: Building automation systems are increasingly represented as semantic knowledge graphs (KGs) using ontologies such as Brick and ASHRAE 223P, creating a m

CAGE-NAS: Certified Functional Descent for Efficient Model Growth

arXiv:2610.01173v1 Announce Type: new Abstract: The progressive growth of neural networks requires deciding when the current representation remains sufficient for optimization and when it should be ex

Calibrating Prediction Timeliness Through Multi-Objective Hyperparameter Optimization for Remaining Useful Life Prediction

arXiv:2610.01530v1 Announce Type: new Abstract: In predictive maintenance, early and late RUL prediction errors carry asymmetric consequences, yet hyperparameter optimization typically targets a singl

Calibration-risk routing for controlled world-model adaptation

arXiv:2610.01001v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) can exploit simulated experience, but a simulator-to-target shift creates a model-selection problem: correctin

safetyarxiv-cs-ai

Can AI Oversight Be Zero Knowledge?

arXiv:2610.01995v1 Announce Type: new Abstract: AI systems increasingly produce outputs from confidential data, such as a fitness-for-duty assessment from medical records or the predicted properties o

Can AI Scientists Coordinate at Runtime?

arXiv:2610.00980v1 Announce Type: cross Abstract: Multi-agent AI scientists have shown improving performance across a diverse range of tasks. Yet a common approach is design-time agentic orchestration

agentsarxiv-cs-ai

Can LLMs Reason Over Long Horizons? An Empirical Evaluation of Context Strategies for Longitudinal Clinical Reasoning

arXiv:2610.00562v1 Announce Type: cross Abstract: Longitudinal clinical reasoning requires large language models (LLMs) to identify and integrate relevant evidence distributed across extended patient

Can LLMs Reliably Annotate Bioassay Metadata to Improve Data Readiness?

arXiv:2610.01616v1 Announce Type: cross Abstract: The emergence of foundation models for molecular property prediction requires a high degree of AI data readiness, including reliable metadata annotati

Capabilities Ain't All You Need: Measuring Propensities in AI

arXiv:2602.18182v5 Announce Type: replace-cross Abstract: AI evaluation has primarily focused on measuring capabilities, with formal approaches inspired from Item Response Theory (IRT) being increasin

Capturing In-Context Learning Dynamics with Task Operators

arXiv:2610.01054v1 Announce Type: cross Abstract: In-context learning (ICL) enables language models to perform new tasks from demonstrations without weight updates. However, every ICL inference requir

CARM: Cancellation-Aware Response Masking for LLM Reinforcement Learning

arXiv:2610.02039v1 Announce Type: cross Abstract: Recent years have witnessed the rapid adoption of reinforcement learning (RL) in large language model (LLM) post-training, with substantial gains in m

safetyarxiv-cs-ai

Hardware

CAST: Cost-Aware Speculative Trees from One-Pass Block Drafters

arXiv:2610.00321v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by drafting future tokens cheaply and verifying them with the target model in parallel

hardwarearxiv-cs-lg

Applications

Causal-Aware Tabular GANs with Reinforcement Learning

arXiv:2510.24046v2 Announce Type: replace-cross Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlook

applicationsarxiv-cs-ai

Causal Memory Policy: Making Memory Utility Identifiable by Intervening on Retrieval

arXiv:2610.02070v1 Announce Type: new Abstract: Memory-augmented large language models must decide which memories to retain, and recent systems do so by estimating each memory's effect on task perform

safetyarxiv-cs-ai

CAVE-Mem: Boundary-Aware Experience Validation for Memory Search

arXiv:2610.00238v1 Announce Type: cross Abstract: Long-term memory agents increasingly rely on it- erative search and reusable experience to answer questions over large personal, factual, or narrative

Certainty Is Not Just Correctness: Rethinking Token-Level Certainty in LLM Reasoning

arXiv:2610.00296v1 Announce Type: cross Abstract: Token-level certainty is widely used as a proxy for correctness in LLM training and inference. However, the performance of certainty-based methods dep

local-aiarxiv-cs-ai

CF-JEPA: Improving Robustness of JEPA World Models via Controllability Factorization

arXiv:2610.00727v1 Announce Type: cross Abstract: Controlling an agent with vision requires being able to separate useful information from irrelevant background information. JEPA-style latent world mo

agentsarxiv-cs-lg

Chaining Skills to Hijack LLM Agents

arXiv:2610.01564v1 Announce Type: cross Abstract: LLM agents use skills to improve performance on specialized tasks. To complete a user request, an agent may invoke several skills in sequence, allowin

ChainLoRA: Geometry-Preserving Task Vector Merging for Continual Learning in LLMs

arXiv:2610.00431v1 Announce Type: cross Abstract: Continual parameter-efficient fine-tuning for large language models (LLMs) must balance retention of previously acquired knowledge, adaptation to new

Characterizing a Configuration Where Inference-Time PRM-Pruned Fragment Grafting Is Inert: Evidence from Three Reasoning LMs

arXiv:2610.00047v1 Announce Type: new Abstract: Diversity collapse in parallel chain-of-thought has motivated inference-time interventions built on a natural design: when a process reward model (PRM)

CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment

arXiv:2606.15396v2 Announce Type: replace-cross Abstract: Malicious content generated from large language models (LLMs) could pose severe safety risks and ethical concerns. While existing LLM safety g

CHORDONOMICON: A Dataset of 666,000 Songs and their Chord Progressions

arXiv:2410.22046v4 Announce Type: replace-cross Abstract: Chord progressions encapsulate important information about music, pertaining to its structure and conveyed emotions. They serve as the backbon

Applications

ChunkVLA-AM: Parallel Action Chunking for Vision-Language-Action Robot Control in Additive Manufacturing

arXiv:2610.01856v1 Announce Type: new Abstract: Vision-language-action (VLA) models unify visual perception, language understanding, and action generation, offering new opportunities for automation in

applicationsarxiv-cs-ro

CineMR: Tool-Integrated Vision-Language Reasoning for Quantitative Cardiac MRI Assessment

arXiv:2610.01166v1 Announce Type: cross Abstract: Cardiovascular magnetic resonance (CMR), including cine imaging, is a reference standard for the noninvasive assessment of cardiac morphology and vent

CLASP: Continual Low-rank Adapters for Spatially Placed Concepts from One Hypernetwork

model-releasesarxiv-cs-cv

arXiv:2610.01331v1 Announce Type: new Abstract: Continual personalization of text-to-image diffusion models requires sequentially acquiring new concepts while retaining previously learned ones. Howeve

Classical Hardness of Learning Functions of Hamiltonians

arXiv:2610.01141v1 Announce Type: cross Abstract: Morohoshi, Nakayama, Manabe, and Mitarai proposed a physically motivated quantum machine learning problem in which the goal is to predict quantities o

Classification Based on Association Rules Algorithm for Breast Cancer

arXiv:2610.00174v1 Announce Type: new Abstract: Breast cancer is a significant contributor to female mortality across the world, displaying one of the highest oc currence rates among the various cance

Clifford Sheaf Neural Networks

arXiv:2610.01322v1 Announce Type: new Abstract: We introduce the Clifford Sheaf Neural Network (CSNN), an equivariant sheaf neural network for geometric graphs that places a Clifford algebra on each s

Clock Diffusion: Efficient Semi-Autoregressive Continuous Diffusion Language Models

arXiv:2610.00894v1 Announce Type: new Abstract: Recent works on continuous diffusion for discrete data have demonstrated performance on par with comparable discrete diffusion models. However, these co

Closed-Loop Refinement and Execution for Learned Driving Planners

arXiv:2610.00992v1 Announce Type: cross Abstract: Learning-based driving planners are usually trained and evaluated in open loop against logged trajectories. In closed loop, a trajectory with small di

researcharxiv-cs-ro

CLoSeR: Closing the Loop for Long-Context Streaming Reconstruction

arXiv:2610.01927v1 Announce Type: new Abstract: Feedforward foundation models have recently shown remarkable 3D reconstruction capabilities. However, existing models exhibit large tracking drift in lo

researcharxiv-cs-cv

Closing the Loop: Practical Training Recipes for Looped Language Models

arXiv:2610.00673v1 Announce Type: cross Abstract: Looped language models increase effective depth by repeatedly applying a shared block of layers, but existing large-scale recipes require multi-stage

Code Owns the Simulation, Jev Owns the Evaluation

arXiv:2610.01834v1 Announce Type: new Abstract: Judgment models such as jev{} return, in a single call and without reasoning text, a probability for each described option. This makes them attractive a

agentsarxiv-cs-ai

Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Software

arXiv:2610.00425v1 Announce Type: cross Abstract: Code generation has emerged as a central capability of large language models, with coding agents now able to produce functionally correct software pro

agentsarxiv-cs-ai

CODesign: Consistency from Data to Trajectory in All-Atom Protein Binder Co-Design

arXiv:2610.01773v1 Announce Type: cross Abstract: The central challenge in de novo protein design is generating plausible, mutually compatible structures and sequences, such that each designed sequenc

local-aiarxiv-cs-ai

CoEvolve: Construct-to-Edit Visual Grounding with Bidirectional State Refinement

arXiv:2610.01710v1 Announce Type: new Abstract: Visual grounding localizes an object described by language with a bounding box. Most multimodal grounding models compress target identification, spatial

Cog-VADU: A Training-Free Cognitive Reasoning Framework for Video Anomaly Detection and Understanding

arXiv:2610.01754v1 Announce Type: cross Abstract: Video Anomaly Detection (VAD) aims to temporally localize abnormal events in videos. Most existing approaches rely on dataset-specific training and cu

local-aiarxiv-cs-ai

ColoACT: Multi-Cue Action Chunking for Smooth Autonomous Colon Navigation on a Self-Propelled Endoscopic Robot

arXiv:2610.01258v1 Announce Type: new Abstract: Autonomous colonoscopic navigation can reduce operator burden and the risk of loop formation or tissue trauma, but remains challenging due to deformable

safetyarxiv-cs-ro

Color Independent Word Segmentation From Transcribed Bangla Passages

arXiv:2610.01191v1 Announce Type: new Abstract: An optical character recognition(OCR) system can scan paper and extract text, making people's jobs easier. While numerous OCR systems are accessible in

researcharxiv-cs-cv

Comedic Fool's Gold: Reward Exploits and Countermeasures in Conversational Humor

arXiv:2610.00197v1 Announce Type: new Abstract: We investigate automated rewards for training language models in conversational humor, focusing on reward exploits and countermeasures. Two approaches a

CommunityKV: Efficient Long-Context Decoding via Graph Partitioning

arXiv:2610.00418v1 Announce Type: new Abstract: Scaling Transformers to long contexts is constrained by the quadratic cost of self-attention and the linear growth of key-value cache memory transfer. S

Comparing a gradient boosting algorithm to the GOES FDC for wildfire detection

arXiv:2610.01994v1 Announce Type: new Abstract: Wildfires pose severe risks to human life, ecosystems, and property. This study presents a machine learning approach for wildfire detection from GOES AB

researcharxiv-cs-cv

Completion Aware Guidance for World Action Models

arXiv:2610.01559v1 Announce Type: cross Abstract: World Action Models (WAMs) predict visual futures and robot actions, yet they remain susceptible to task-incomplete imagination, where plausible, acti

CompMat-Bench: Benchmarking AI Agents for Computational Materials Science

arXiv:2610.00636v1 Announce Type: new Abstract: Evaluating AI agents on scientific research tasks is constrained by the time and resources required for the underlying experiments or calculations. In c

Compositional Embedding Architecture for Physical Field Prediction in Componentized Aerospace Systems

arXiv:2610.00237v1 Announce Type: cross Abstract: Spacecraft thermal design requires repeated evaluation of how variations in the number and spatial arrangement of heat-generating components and in th

local-aiarxiv-cs-lg