Search: “papers”

When Financial Fine-tuning Fails: A Three-Level Detectability Analysis of Numerical Hallucination in Domain-Adapted Language Models

arXiv:2609.04806v1 Announce Type: new Abstract: Financial large language models are increasingly deployed for summarization of reports and disclosures, where numerical hallucination poses significant

7 Sept 2026

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Tutorials

Why We Care About Understanding: Competence through Predictive Compression

DGX agent

arXiv:2609.04962v1 Announce Type: new Abstract: What is the relation between understanding and compression, and why does human understanding take such a heavily compressed form? Across information the

tutorialsarxiv-cs-ai

7 Sept 2026

Local Ai

A hybrid pipeline for dynamic ontology-based semantic mapping

arXiv:2609.03891v1 Announce Type: new Abstract: Semantic mapping plays a crucial role in the ability of a robot to interact with objects, operate and navigate a complex environment. The most common pi

local-aiarxiv-cs-ro

A Large Open Multi-Energy Corpus of Soil Compaction Tests, with Machine-Learning Baselines

arXiv:2609.03337v1 Announce Type: new Abstract: Every engineered fill is specified by a maximum dry density and an optimum moisture content. Each determination needs a full Proctor test. Published cor

Applications

An Adversarial Zero-Shot Learning Approach for Anomaly Detection in Multivariate IoT Traffic Data

arXiv:2609.03505v1 Announce Type: new Abstract: Anomaly detection in Internet of Things (IoT) networks presents unique challenges due to the diversity of devices, lack of labeled data, and domain vari

applicationsarxiv-cs-lg

Anisotropic View Distance Metric for High-Dimensional Data: Theory, Geometry, and Fast Computation

arXiv:2206.05215v2 Announce Type: replace Abstract: K-Means clustering algorithm is one of the most commonly used clustering algorithms because of its simplicity and efficiency. K-Means clustering alg

researcharxiv-cs-lg

Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models

arXiv:2603.16718v2 Announce Type: replace Abstract: LLMs perform strongly across NLP, but their ability to produce explicit grammatical analyses remains unclear. Arabic provides a challenging testbed

researcharxiv-cs-cl

Artificial Intelligence for Energy Optimization in Data Centers

arXiv:2609.03716v1 Announce Type: new Abstract: Data centers are increasingly optimized by artificial intelligence and, at the same time, increasingly loaded by it. The literature treats these as two

ARTiS: An Adaptive Robotic Gripper for Enhanced Tool Manipulation in Disassembly Applications

arXiv:2609.03362v1 Announce Type: new Abstract: Grasping and holding tools while using them presents a considerable challenge not only for robots but also for humans. Such a challenge is particularly

researcharxiv-cs-ro

Local Ai

Automated Weld Seam Recognition and 3D Mapping for Robotic Post Processing Using Photogrammetry and Semantic Segmentation

arXiv:2609.03970v1 Announce Type: new Abstract: Accurate identification of weld seam geometries is essential for automated robotic post processing operations such as grinding, finishing, and inspectio

local-aiarxiv-cs-ro

BASP: Communication-Efficient Batch-Aware Sequence Parallelism for LLM Training

arXiv:2609.03151v1 Announce Type: cross Abstract: Long-context reasoning for large language models (LLMs) is becoming increasingly important, but training over long sequences remains challenging due t

Beyond BLEU: A Case for Redefining Sign Language Translation Benchmarks

arXiv:2609.03734v1 Announce Type: cross Abstract: BLEU-4 is the standard metric for evaluating sign language translation (SLT), but spoken-language metrics may not adequately reflect sign language pro

BharatGather: A Culturally-Informed Benchmark Dataset for Misinformation and Fake News Detection in Indian Public Events

model-releasesarxiv-cs-cl

arXiv:2609.02895v1 Announce Type: new Abstract: Large-scale public events, such as religious festivals, political rallies, and cultural gatherings, are increasingly vulnerable to the rapid disseminati

Comparing Retrieval Methods for Academic Advisor Discovery: A Six-Method Study of 768 CS Faculty Profiles Across 9 US Universities

arXiv:2609.03901v1 Announce Type: cross Abstract: We present a comparative evaluation of six information retrieval methods for the task of academic advisor discovery: ranking CS faculty members by rel

Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks

arXiv:2609.03977v1 Announce Type: cross Abstract: Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent

Counterexamples as Feedback for Agent Self-Correction

arXiv:2609.02892v1 Announce Type: cross Abstract: Single-turn code-generation metrics understate a central property of deployed agents: whether they can repair a wrong artifact after receiving concret

agentsarxiv-cs-ai

Tutorials

Dancing with REEM-C: A robot-to-human physical-social communication study

arXiv:2408.05301v3 Announce Type: replace Abstract: Humans often work closely together and relay a wealth of information through physical interaction. Robots, on the other hand, are not yet able to wo

tutorialsarxiv-cs-ro

Differentially private federated learning with Byzantine-robust aggregation: A cross-domain framework for secure model training in banking and healthcare systems

arXiv:2609.03064v1 Announce Type: cross Abstract: Federated learning allows banks, hospitals, and other regulated organizations to train a shared model without moving raw records off their own servers

DogLegs: Robust Proprioceptive State Estimation for Legged Robots Using Multiple Leg-Mounted IMUs

arXiv:2503.04580v3 Announce Type: replace Abstract: Robust and accurate proprioceptive state estimation of the main body is crucial for legged robots to execute tasks in extreme environments where ext

researcharxiv-cs-ro

DropClick: Semi-Automated One-Click Segmentation for Agricultural Robotic Data

arXiv:2609.03680v1 Announce Type: new Abstract: Labelling vision datasets, especially for segmentation tasks, is a laborious and costly process that stymies novel developments in agricultural robotics

Local Ai

DSAQuant: Denoising-Stage-Aligned Quantization-Aware Training for Video Generation

arXiv:2609.04031v1 Announce Type: new Abstract: Video diffusion models (VDMs) have achieved impressive progress in text-to-video generation, but their high memory and computational costs hinder practi

local-aiarxiv-cs-cv

Dual-Form ASR: Semantics-Aware Inverse Text Normalization for Chinese Speech Recognition

arXiv:2609.02901v1 Announce Type: new Abstract: Modern automatic speech recognition (ASR) scenarios require both spoken-form transcripts for faithful transcription and readable written-form transcript

researcharxiv-cs-cl

Environment Evolution for Terminal Agents

arXiv:2609.04128v1 Announce Type: new Abstract: Scaling interactive and verifiable environments is critical for training terminal agents. As frontier models become more capable, environments synthesiz

Extracting Forgotten Prompts from Targeted Unlearned Models

arXiv:2609.03662v1 Announce Type: new Abstract: Recent unlearning methods (e.g. NPO, DPO, LUNAR) make use of refusal alignment to suppress forgotten data. However, it has been shown that refusal respo

safetyarxiv-cs-lg

Applications

Following a Unique Path: A Fast Certifier Applied to Outlier-Robust Pose Registration

arXiv:2609.03222v1 Announce Type: new Abstract: Certifiable methods have arisen as a means to guarantee global optimality of solutions to non-convex problems using convex semidefinite programming (SDP

applicationsarxiv-cs-ro

FoRIS: Progressive Foreground Refinement for Training-Free In-Context Segmentation

arXiv:2609.03384v1 Announce Type: new Abstract: In-Context Segmentation (ICS) aims to precisely segment arbitrary semantic concepts, such as objects or parts, given one or a few annotated visual exemp

From Prior-Guided Heuristics to Deployable Agents: Accelerating Demonstration-Driven Reinforcement Learning for Deadline-Constrained Network Control

arXiv:2609.03590v1 Announce Type: cross Abstract: Timely delivery of delay-sensitive information over dynamic, heterogeneous networks is essential for NextG interactive applications, yet providing str

Applications

Genetic Algorithms for Tractable Bayesian Network Fusion via Pre-Fusion Edge Pruning

arXiv:2609.03724v1 Announce Type: cross Abstract: Bayesian Network (BN) fusion combines multiple input networks into a single structure, balancing dependency preservation with computational tractabili

applicationsarxiv-cs-lg

Hardware

GPU-Accelerated Astrodynamics World Models for Spacecraft Rendezvous and Proximity Operations

arXiv:2609.03067v1 Announce Type: new Abstract: World models are an emerging paradigm in representation learning in which an agent jointly learns state-action dynamics and observation models from offl

hardwarearxiv-cs-ro

Grammar-Aligned Decoding

arXiv:2405.21047v4 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with reliably generating highly structured outputs, such as program code, mathematical formulas, or well-forme

Tutorials

Guide, Not Bind: Why Defeasible Priors Fail in Augmented Lagrangian Causal Discovery

arXiv:2609.03442v1 Announce Type: new Abstract: Differentiable causal discovery methods increasingly encode expert priors as forbidden-edge constraints enforced by an Augmented Lagrangian (ALM) penalt

tutorialsarxiv-cs-lg

IndicSafeEval: Safety Robustness of Large Language Models under Multilingual Persuasive Jailbreak Attacks

arXiv:2609.03781v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in multilingual settings, yet their safety is still evaluated primarily in English. This limits our

Inferring Affective Consciousness in an Artificial Agent: A Case Study

arXiv:2609.03883v1 Announce Type: new Abstract: Creatures that display 'hedonic place preference behaviour' are thought by many scientists to experience feelings, on the assumption that their attracti

agentsarxiv-cs-ai

K-NeAS: Scalable Multi-Material CT Reconstruction Using Neural SDFs

arXiv:2607.14415v2 Announce Type: replace Abstract: Computed Tomography (CT) carries significant ionizing radiation risks, driving the need for sparse-view reconstruction. Implicit scene representatio

Learning-based Adaptive Safety-Critical Control With Evolving Unsafe Regions

arXiv:2503.16551v4 Announce Type: replace Abstract: Control barrier functions (CBFs) provide a principled framework for safety-critical control, but their construction typically requires an explicit a

safetyarxiv-cs-ro

Local Path Planning and Obstacle Avoidance for an Omnicopter Platform

arXiv:2609.03630v1 Announce Type: new Abstract: Autonomous unmanned aerial vehicles (UAVs) increasingly operate in cluttered environments where global planners such as RRT* are not directly deployable

agentsarxiv-cs-ro

Lose the Order, Keep the Hierarchy: Deordering HTN Plans

arXiv:2609.03912v1 Announce Type: new Abstract: Hierarchical Task Network (HTN) planning is a powerful planning formalism based on task decomposition. Although most of the literature studied plan gene

LRConv-NeRV: Low Rank Convolution for Efficient Neural Video Compression

arXiv:2603.18261v2 Announce Type: replace-cross Abstract: Neural Representations for Videos (NeRV) encode entire video sequences within neural network parameters, offering an alternative paradigm to c

Medical Reasoning in the Era of LLMs: A Systematic Review of Enhancement Techniques and Applications

arXiv:2508.00669v2 Announce Type: replace-cross Abstract: The proliferation of Large Language Models (LLMs) in medicine has enabled impressive capabilities, yet a critical gap remains in their ability

agentsarxiv-cs-ai

Mixed Data Clustering Survey and Challenges

arXiv:2512.03070v2 Announce Type: replace-cross Abstract: The advent of the big data paradigm has transformed how industries manage and analyze information, ushering in an era of unprecedented data vo

Neural Video Compression Based on Deformable Temporal Alignment and Difference-aware Fusion

arXiv:2609.03520v1 Announce Type: cross Abstract: In conditional coding-based neural video compression, the quality of temporal context directly affects compression per- formance. Existing methods mos

Tutorials

OBER+: Continuity-Aware Reporting and Traceable Continuous Improvement in Outcome-Based Education

arXiv:2609.03770v1 Announce Type: cross Abstract: Institutions practising outcome-based education compute learning outcome attainment routinely, while reviews of curriculum analytics report an absence

tutorialsarxiv-cs-cl

Off the Planckian Locus: Using 2D Chromaticity to Improve In-Camera Color

arXiv:2511.17133v4 Announce Type: replace Abstract: Traditional in-camera colorimetric mapping relies on correlated color temperature (CCT)-based interpolation between pre-calibrated transforms optimi

Hardware

Para-Pipe: Exploiting Hierarchical Operator Parallelism of ML Computational Graphs on SoCs

arXiv:2609.04168v1 Announce Type: cross Abstract: As edge-based deep learning applications become more complex, optimizing performance on heterogeneous System-on-Chips (SoCs) presents unique challenge

hardwarearxiv-cs-lg

PeroMAS: A Multi-agent System of Perovskite Material Discovery

arXiv:2602.13312v2 Announce Type: replace-cross Abstract: As a pioneer of the third-generation photovoltaic revolution, Perovskite Solar Cells (PSCs) are renowned for their superior optoelectronic per

PPO-STGNN: A Proximal Policy Optimization Approach with Spatio-Temporal Graph Neural Networks for DAG Task Scheduling in Cloud-Edge-End Computing

arXiv:2609.03503v1 Announce Type: new Abstract: With the rapid development of the Internet of Things, computation intensive directed acyclic graph (DAG) tasks have become increasingly common in cloud-

Predictive Zonotope Reduction: Precise Runtime Monitoring under Uncertainty

arXiv:2609.03699v1 Announce Type: new Abstract: Robots operating in physical environments make control decisions based on uncertain sensor measurements, which can lead to unsafe or suboptimal actions.

safetyarxiv-cs-ro

Preprocessing Failure and Adversarial Detection in Depthwise-Separable Edge Vision Systems

arXiv:2609.03453v1 Announce Type: new Abstract: Preprocessing-based defenses are the standard first-line response to adversarial attacks on edge vision systems, requiring no retraining, no architectur