All entries

Dynamic language model representations for multi-objective reaction optimisation

arXiv:2609.11790v1 Announce Type: new Abstract: Optimising chemical reactions across multiple objectives, such as yield, selectivity, and safety, is central to chemical synthesis, and model-driven app

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

E-CONAN (Entailment, CONtradition And Neutral) Benchmarks: Arabic Textual Entailment and Natural Inference Datasets

DGX agent

arXiv:2609.11334v1 Announce Type: new Abstract: Natural Language Inference processes pairs of sentences to extract their semantic relations. NLI has been a hot research topic, integrated as a main com

model-releasesarxiv-cs-cl

11 Sept 2026

EGGROLL, Unrolled: Understanding and Improving Low-Rank Evolution Strategies at Scale

arXiv:2609.10980v1 Announce Type: new Abstract: EGGROLL makes evolution strategies (ES) practical for LLMs by replacing dense Gaussian weight perturbations with low-rank Gaussian products, often of ra

local-aiarxiv-cs-lg

Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support

model-releasesarxiv-cs-ai

arXiv:2609.10421v1 Announce Type: cross Abstract: Background: Emergency Department (ED) return visits are commonly reviewed for quality assurance, but are often limited (e.g., to revisits within 48-72

Agents

Emergent Risks in Generative Multi-Agent Systems

arXiv:2603.27771v3 Announce Type: replace-cross Abstract: Multi-agent systems composed of large generative models are rapidly moving from laboratory prototypes to real-world deployments, where they jo

agentsarxiv-cs-cl

EMMI: Edge Multi-Modal Intelligence for Communication-Efficient MLLM Inference via Fused Representation Compression

arXiv:2609.11058v1 Announce Type: new Abstract: Recent advances in multimodal large language mod- els (MLLMs) have opened new opportunities for edge intelligence by enabling reasoning across heterogen

Empirical Evaluation of Data Poisoning Attacks in Supervised Learning

arXiv:2609.10952v1 Announce Type: cross Abstract: Data poisoning corrupts training data to degrade a model or to plant attacker-controlled behavior. This study evaluates two representative training-ti

Empirical Evaluation of Membership Inference Attacks on NLP Text Classifiers: A Baseline Study on SST-2

model-releasesarxiv-cs-cl

arXiv:2609.10935v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) try to determine whether a specific record was used to train a model, a privacy risk that matters in natural langu

Enabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN)

arXiv:2609.11569v1 Announce Type: cross Abstract: We present EXYGEN (EXplore Your Graphs ENgine), a framework for knowledge graph (KG) understanding that enables conversational access to KGs at scale.

Epistemic orientation predicts legislative effectiveness among members of the US Congress

arXiv:2609.11865v1 Announce Type: new Abstract: Truth and evidence-based communication provide important foundations for democratic governance, accountability, and collective decision-making. Prior wo

researcharxiv-cs-cl

Equity Promotion in Online Resource Allocation

arXiv:2112.04169v3 Announce Type: replace-cross Abstract: We consider online resource allocation under a typical non-profit setting, where limited or even scarce resources are administered by a not-fo

researcharxiv-cs-ai

Estimating Inconsistency Response Surfaces under Uncertainty in Cyber-Physical System Development

arXiv:2609.11331v1 Announce Type: new Abstract: Cyber-Physical Systems (CPS) are commonly represented through multiple interconnected models. During development, CPS consistency requires that shared m

Evaluating LLM-Simulated Conversations in Modeling Inconsistent and Uncollaborative Behaviors in Human Social Interaction

model-releasesarxiv-cs-cl

arXiv:2603.17094v2 Announce Type: replace Abstract: Simulating human conversations using large language models (LLMs) has emerged as a scalable methodology for modeling human social interaction. This

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

arXiv:2609.11872v1 Announce Type: cross Abstract: Continuous glucose monitoring (CGM) provides high-frequency measurements of glucose dynamics and enables short-term glucose forecasting for diabetes m

Evaluation of Vision-Language Models Across Diverse Coastal Environments

arXiv:2609.10855v1 Announce Type: new Abstract: Vision-language models (VLMs) enable robotic per- ception by associating visual observations with natural-language concepts. Yet their performance in co

safetyarxiv-cs-cv

Evidence for Limited Metacognition in LLMs

arXiv:2509.21545v3 Announce Type: replace Abstract: The possibility of LLM self-awareness and even sentience is gaining increasing public attention and has major safety and policy implications, but th

EVPeriscope: Extended Perception across Aerial and Ground Vehicles with Event-based Propeller Tracking

arXiv:2609.11920v1 Announce Type: new Abstract: Reliable relative localization between aerial and ground robots is a key requirement for tightly coordinated heterogeneous teams. This can be difficult

researcharxiv-cs-ro

EVTradeMatch: A Mobility-Aware Multi-Objective Matching Framework for EV--EV Energy Trading

arXiv:2609.10551v1 Announce Type: cross Abstract: Peer-to-peer energy trading among electric vehicles (EVs) can improve charging flexibility under limited charging infrastructure, but effective EV--EV

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

arXiv:2609.11860v1 Announce Type: cross Abstract: Energy consumption forecasting relies on increasingly complex machine learning (ML) models, such as Genetic Programming-based symbolic regressors, who

Exponential Pixelating Integral transform with dual fractal features for enhanced chest X-ray abnormality detection

arXiv:2609.10988v1 Announce Type: cross Abstract: The heightened prevalence of respiratory disorders, particularly exacerbated by a significant upswing in fatalities due to the novel coronavirus, unde

local-aiarxiv-cs-cv

Applications

Expressive Robotic Pianist: Mastering Complex Piano Repertoire with Graph-Mimic and Musical Dynamics

arXiv:2609.10844v1 Announce Type: new Abstract: Enabling robots to perform musical instruments with human-level expressivity represents a frontier in bridging the gap between mechanical precision and

applicationsarxiv-cs-ro

Agents

ExpTest: Loss-Curve Hypothesis Testing for Autonomous Learning-Rate Selection in Deep Neural Networks

arXiv:2411.16975v2 Announce Type: replace Abstract: Hyperparameter tuning remains a significant challenge in the training of deep neural networks (DNNs), requiring manual search or time-intensive grid

agentsarxiv-cs-lg

FARM: Reading Failure Signals from the Internal Predictive States of a Frozen Robotic World Model

model-releasesarxiv-cs-ro

arXiv:2609.11445v1 Announce Type: new Abstract: Reliable robot deployment requires online failure monitoring, yet existing monitors mainly derive risk from proxy signals or train dedicated monitoring

Fast and Accurate Monomodal 3D High Resolution Deep Registration of Drosophila Larval Brain Volumes

model-releasesarxiv-cs-cv

arXiv:2609.11240v1 Announce Type: new Abstract: The larval stage of Drosophila melanogaster is a compact model system for neuroscience whose genetic toolkit allows fluorescent markers to be expressed

FastMap: Real-Time Semantic Map Completion via Bitwise Masked Modeling

model-releasesarxiv-cs-cv

arXiv:2506.07350v2 Announce Type: replace-cross Abstract: Semantic map completion, which predicts the layout of unobserved regions from partial observations, is a critical capability for indoor robot

Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems

arXiv:2609.09980v1 Announce Type: cross Abstract: High Performance Computing-Quantum Computing (HPCQC) platforms expose multiple Quantum Processing Units (QPUs) that may differ in size, topology, nati

researcharxiv-cs-ai

Fisher-Rao Gradient Flows of Linear Programs and State-Action Natural Policy Gradients

arXiv:2403.19448v3 Announce Type: replace-cross Abstract: Kakade's natural policy gradient method has been studied extensively in recent years, showing linear convergence with and without regularizati

FlexComp: One Model for Every Ratio in Context Compression

arXiv:2609.11192v1 Announce Type: new Abstract: Soft context compression condenses a context into a few memory tokens that a frozen LLM consumes in place of the raw text, but existing compressors fix

researcharxiv-cs-cl

Flow Duality and Source Geometry for Categorical Generation

arXiv:2609.10863v1 Announce Type: new Abstract: Continuous and discrete flow matching are usually treated as separate constructions. This paper identifies a duality between them: projecting continuous

Fortunate Recall: Ontology-Driven Memory Lifecycle Management for Persistent Coherence in LLMs

model-releasesarxiv-cs-ai

arXiv:2609.10413v1 Announce Type: new Abstract: Current LLM memory systems treat all personal facts identically, so stores grow without bound while retrieval precision degrades. The core challenge is

FreeFlow: A Bias-free Hierarchical Transformer for Optical Flow Estimation

arXiv:2609.11486v1 Announce Type: new Abstract: Optical flow methods typically rely on task-specific inductive biases, such as correlation volumes, feature warping, and iterative refinement, among oth

local-aiarxiv-cs-cv

Agents

Freehand Sketching for End-User Programming of Robot Swarms

arXiv:2609.11078v1 Announce Type: new Abstract: Robot swarms are increasingly used in applications where accessible interaction with non-expert users is desirable. This paper investigates freehand ske

agentsarxiv-cs-ro

From Connectivity to Rewards: Dense Reward Learning with Directed State Graphs

arXiv:2609.10781v1 Announce Type: new Abstract: The integration of graphs with Goal-Conditioned Hierarchical Reinforcement Learning (GCHRL) has received increasing attention, as graphs naturally encod

From Cycle Space to Cycle Manifold: Limits and Achievability of Blind False Data Injection Attacks

arXiv:2609.10631v1 Announce Type: cross Abstract: A false data injection attack (FDIA) can change the estimated grid state while evading a residual-based bad data detector (BDD). Existing blind attack

From Evaluation to Enhancement: Benchmarking and Improving Think-with-Video Reasoning for Video Generative Models

model-releasesarxiv-cs-cv

arXiv:2609.11242v1 Announce Type: new Abstract: Video generation has advanced to produce visually compelling and temporally coherent results. Yet, whether these models can genuinely think with video--

From Protocols to Evidence: Bounded Claims for AI in Service of the Common Good

arXiv:2609.11910v1 Announce Type: new Abstract: Artificial Intelligence does more than create a governance problem. It can also reveal where institutions have already failed to provide responsiveness,

From Repetition to Recognition: Inductive Discovery of Disinformation Narratives

arXiv:2609.11128v1 Announce Type: new Abstract: In disinformation datasets, narratives are often understood as recurring interpretive patterns that group texts under narrative labels. Recent work form

researcharxiv-cs-cl

From State Synchronization to Cognitive Self-Evolution: An Operational Architecture for Cognitive Digital Twins

arXiv:2609.09625v1 Announce Type: new Abstract: As Digital Twin (DT) systems evolve beyond state synchronization toward task-oriented and knowledge-driven operation, Cognitive Digital Twins (CDTs) hav

researcharxiv-cs-ai

Gait-Dependent Effects on Quadruped Locomotion for Load-Carrying using Passive Mechanism

arXiv:2609.11059v1 Announce Type: new Abstract: Passive mechanical interfaces offer a lightweight alternative to actuated manipulators for quadruped payload carrying, but their impedance directly coup

researcharxiv-cs-ro

General Quantification of Covariate and Concept Shifts

arXiv:2609.11918v1 Announce Type: new Abstract: Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bound theory is limited to narrow, id

Generalization Analysis of Distributed Kernel-based Robust Gradient Descent Algorithms

arXiv:2609.11712v1 Announce Type: cross Abstract: In this paper, we investigate the generalization performance of distributed gradient descent algorithms in a reproducing kernel Hilbert space under a

Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis

arXiv:2506.00849v2 Announce Type: replace Abstract: Despite the empirical success of Diffusion Models (DMs) and Variational Autoencoders (VAEs), their generalization performance remains theoretically

Generalized Score Matching for Parameter Estimation on Convex Domains

arXiv:2609.11521v1 Announce Type: new Abstract: Maximum likelihood (ML) estimation is a principled and statistically efficient approach for learning probabilistic models. However, for unnormalized mod

Generative AI for Analysts

model-releasesarxiv-cs-ai

arXiv:2512.19705v2 Announce Type: replace-cross Abstract: We study how generative artificial intelligence (GenAI) reshapes financial analysts' information production. Using the 2023 integration of Gen

Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

arXiv:2609.11915v1 Announce Type: cross Abstract: Generative artificial intelligence changes how firms reach customers, but standard marketing data do not record how often users see and notice a firm'

Generative Replay Mitigates Sample Starvation in Quantum Architecture Search

arXiv:2609.11248v1 Announce Type: cross Abstract: Reinforcement learning (RL) can automate quantum architecture search, but its scalability is limited when useful circuit trajectories become rare in t

local-aiarxiv-cs-lg

Geospatial Foundation Models Capture Health-Relevant Dimensions of Place Beyond Conventional Social Risk Indices

arXiv:2609.11689v1 Announce Type: cross Abstract: Area-based social risk indices summarize residents' socioeconomic conditions but incompletely capture physical features of place that may affect healt

Tutorials

GEOSTEER: Geodesic Optimization for Activation Steering in Large Language Models

arXiv:2609.10658v1 Announce Type: new Abstract: Activation steering provides a lightweight way to control large language models (LLMs) by modifying their hidden activations at inference time. Among th

tutorialsarxiv-cs-lg