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Improving Natural-Language Combinatorial-Optimization Accuracy in Resource-Constrained Language Models via Formal Abstractions

arXiv:2608.18409v1 Announce Type: new Abstract: Combinatorial scheduling poses a significant challenge for language models, requiring them to identify feasible solutions within exponentially large sea

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Safety

Improving Rural Medication Safety with AI: A Scoping Review

DGX agent

arXiv:2608.18135v1 Announce Type: new Abstract: Introduction: Medication errors (MEs) represent a significant threat to global healthcare systems, contributing to patient harm. Introducing artificial

safetyarxiv-cs-ai

20 Aug 2026

Inference and Uncertainty Quantification for Streaming r-PCA

arXiv:2608.18374v1 Announce Type: cross Abstract: We address two open questions in streaming PCA via Oja's algorithm: sharp operator-norm convergence for general rank under sub-Gaussian data, and dist

Infrared Universality of Collective Dynamics across Transformer and State-Space Architectures

arXiv:2608.18592v1 Announce Type: new Abstract: Whether distinct neural architectures develop common collective dynamics remains an open question. Recent analysis of Transformer language models reveal

Institutional Books - Enriched Text: A customizable multilingual open-source pipeline for denoising, deduplicating, and annotating OCR text at scale

arXiv:2608.19026v1 Announce Type: new Abstract: Released in 2025, Institutional Books: Harvard Library (IB-HL) is a collection of 983,004 volumes (242B o200k_base tokens), originally digitized through

Institutional Books - Visual Elements: An open-source pipeline for extracting, classifying, deduplicating, and captioning visual elements from digital book collections

arXiv:2608.18957v1 Announce Type: new Abstract: Historical book collections contain rich visual elements - such as illustrations, photographs, engravings, and decorative art - that are frequently unde

researcharxiv-cs-cv

Institutional Newspapers Pipeline: Deriving billions of high quality tokens from historical newspapers

arXiv:2608.18972v1 Announce Type: new Abstract: Historical newspapers are an abundant record of public life, but their dense, irregular and sometimes noisy layouts make computational access to these m

Institutional Prestige as Geographic Bias in Large Language Models: Evidence from Three Factorial Experiments with Bootstrap Confidence Intervals

arXiv:2608.18107v1 Announce Type: cross Abstract: We investigate whether large language models (LLMs) systematically discriminate in candidate evaluations based on applicant name ethnicity and/or inst

safetyarxiv-cs-ai

Interactive Stroke-based Neural SDF Sculpting

arXiv:2502.02891v2 Announce Type: replace-cross Abstract: Recent advances in implicit neural representations have made them a popular choice for modeling 3D geometry. However, directly editing these r

researcharxiv-cs-cv

Intercepting the Kangaroo: Experimental Astrolinguistics with Constructed Lexicons, Active Probing, and Large Language Models as Informants and Hypothesis Proposers

arXiv:2608.19124v1 Announce Type: cross Abstract: Astrolinguistics -- communication with minds that categorize reality differently from ours -- has been purely speculative since Freudenthal's Lincos (

Interpretable AI predicts a 2026 summer dry anomaly in central China

arXiv:2608.19163v1 Announce Type: cross Abstract: Seasonal precipitation anomalies are largely regulated by atmospheric circulation, which dynamical models predict with greater reliability than precip

Introducing the Privacy-HSD Trade-off: Hate Speech Detection, but not at the Cost of Privacy

arXiv:2608.19006v1 Announce Type: new Abstract: Hate speech is a real and timely threat that affects a large portion of online users, especially youth and minority groups. While building reliable and

Iterative Flow Matching: Path Correction and Gradual Refinement for Enhanced Generative Modeling

arXiv:2502.16445v4 Announce Type: replace-cross Abstract: Generative models for image generation are now commonly used for a wide variety of applications, ranging from guided image generation for ente

Jailbreaking in the Haystack

arXiv:2511.04707v2 Announce Type: replace-cross Abstract: Recent advances in long-context language models (LMs) have enabled million-token inputs, expanding their capabilities across complex tasks lik

JSL-DC: A Word-Level Japanese Sign Language Dataset with Linguist-Derived Descriptions for Distinguishing Confusable Signs

model-releasesarxiv-cs-cv

arXiv:2608.18412v1 Announce Type: new Abstract: Effective sign language (SL) acquisition is crucial for deaf children, yet 95% are born to hearing parents who often lack proficiency in SL. SL recognit

KA2L: A Knowledge-Aware Active Learning Framework for LLMs

arXiv:2603.17566v2 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) with high-quality knowledge has been shown to enhance their performance effectively. However, there is a pa

researcharxiv-cs-cl

LabDex: A Hierarchical Benchmark for Dexterous Manipulation in Laboratories

model-releasesarxiv-cs-ro

arXiv:2608.18618v1 Announce Type: new Abstract: Autonomous laboratories hold great promise for accelerating scientific discovery. To achieve this vision, robots are supposed to dexterously manipulate

LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum

arXiv:2601.01684v2 Announce Type: replace-cross Abstract: While dense retrieval models have been the standard for state-of-the-art information retrieval, their deployment is often constrained by high

Language Models for Portuguese: A Systematic Mapping Study

arXiv:2608.18138v1 Announce Type: cross Abstract: In recent years, the rapid development of language models has transformed the field of Natural Language Processing through a wide range of application

Large Language Model for Verilog Code Generation: Literature Review and the Road Ahead

arXiv:2512.00020v3 Announce Type: replace-cross Abstract: Code generation has emerged as a critical research area at the intersection of Software Engineering (SE) and Artificial Intelligence (AI), att

safetyarxiv-cs-ai

Applications

Large Language Models in Mental Health: A Systematic Review of Applications, Innovations, and Ethical Challenges

arXiv:2608.18080v1 Announce Type: new Abstract: We present a review on the applications of large language models (LLMs) in health, e.g., social media analysis, clinical conversational agents, therapy

applicationsarxiv-cs-ai

Latent Space Refusal Anchoring for Low-Resource African Languages: Mechanistic Safety Recovery Without Retraining

arXiv:2608.18089v1 Announce Type: cross Abstract: Instruction-tuned models often refuse harmful requests in English but comply with the same requests in Yoruba, Igbo, Igala, and Hausa. This suggests t

Leaf Values as Coordinates: Exact Contrastive Explanation for Gradient-Boosted Ensembles

arXiv:2608.19127v1 Announce Type: cross Abstract: A gradient-boosted ensemble predicts by summing one leaf value per tree. Read those values as coordinates rather than as intermediate results, and eve

Learned, Then Lost: A Measured Single-Example Counterfactual in Pre-training

arXiv:2608.19168v1 Announce Type: new Abstract: A single training example's contribution to a finished model is normally estimated rather than measured, because measuring it takes two expensive full p

safetyarxiv-cs-lg

Learning Canonical Register Automata over Ordered Data Domains

arXiv:2608.18765v1 Announce Type: new Abstract: Register automata are finite automata equipped with memory that recognize data languages over infinite alphabets. In this work, we investigate active le

researcharxiv-cs-cl

Learning Random Geometric Graphs Drawn in Probabilistic Metric Spaces

arXiv:2608.19082v1 Announce Type: cross Abstract: We present a new data-driven learning of a Random Geometric Graph (RGG) of a multivariate dataset, where the graph is drawn in a probabilistic metric

Tutorials

Learning-State-Aware Dynamic Generative Data Augmentation on Small-Scale Datasets

arXiv:2608.18907v1 Announce Type: cross Abstract: Small-scale image classification is often limited by the scarcity of training data. Generative data augmentation (GDA) based on pretrained generative

tutorialsarxiv-cs-ai

Tutorials

Learning Topological Features of widehat Z-invariants

arXiv:2608.18570v1 Announce Type: cross Abstract: Machine learning and data analysis techniques have recently emerged as powerful tools for identifying patterns and formulating conjectures in mathemat

tutorialsarxiv-cs-lg

Learning What to Fail On: Failure-Mode Contextual Bandits for Adversarial Data Curation

arXiv:2608.18681v1 Announce Type: new Abstract: We introduce a failure-aware adversarial retrieval-augmented framework for improving robustness in natural language understanding. Rather than selecting

safetyarxiv-cs-cl

Agents

LEDGER: Claim-to-Evidence Trace Graphs for Auditing LLM Agents

arXiv:2608.18398v1 Announce Type: cross Abstract: Large language model (LLM) agents can now carry out long-horizon technical workflows involving complex tool use, code execution, file edits, and gener

agentsarxiv-cs-ai

Levy Attention: Single-Pass Predictive Uncertainty for Continuous-Time Attention

arXiv:2608.19171v1 Announce Type: new Abstract: Deep models for irregularly-sampled time series answer queries at arbitrary continuous timestamps, yet report nothing about how far each answer should b

Listening or Reading? Evaluating Speech Awareness in Chain-of-Thought Speech-to-Text Translation

arXiv:2510.03115v2 Announce Type: replace Abstract: Speech-to-Text Translation (S2TT) systems built from Automatic Speech Recognition (ASR) and Text-to-Text Translation (T2TT) modules face two major l

researcharxiv-cs-cl

Hardware

LLM-Powered Predictive Decision-Making for Sustainable Data Center Operations

arXiv:2608.18503v1 Announce Type: new Abstract: The growing demand for AI-driven workloads, particularly from Large Language Models (LLMs), has raised concerns about the significant energy and resourc

hardwarearxiv-cs-lg

LongNovel: A Multi-Scale Benchmark for Hallucination Detection in Long-Context Novel Summarization

arXiv:2608.18082v1 Announce Type: new Abstract: Although context windows have expanded significantly in recent years, hallucinations in long-context summarization remain a challenge. Long novels are b

Look Clearly Before Answering: Mitigating Hallucinations in LVLMs via Saliency-Driven Perceptual Realignment

arXiv:2607.16841v2 Announce Type: replace Abstract: Large vision-language models (LVLMs) have demonstrated remarkable capabilities in multimodal understanding. However, they remain prone to hallucinat

safetyarxiv-cs-cv

Agents

Looped Language Models Improve Compositional Tool Calling

arXiv:2608.18171v1 Announce Type: new Abstract: Looped language models have shown promising results on reasoning benchmarks, yet their potential for agentic tool use remains largely unexplored. We stu

agentsarxiv-cs-ai

Lost in Aggregation: How Benchmarks Overlook Irreplaceable Model Strengths

model-releasesarxiv-cs-lg

arXiv:2608.18919v1 Announce Type: new Abstract: Tabular machine learning benchmarks typically summarize performance by averaging scores, ranks, or pairwise wins across datasets. Such aggregates are us

Low-Power, Neuromorphic, Acoustic Anomaly Detection for Persistent Machine Monitoring

arXiv:2608.18341v1 Announce Type: cross Abstract: Persistent acoustic monitoring can detect machine faults without physical contact, but always-on inference is constrained by power, latency, and deplo

LT-Mem: Volatility-Aware Spatio-Temporal Memory for Lifelong Scene Understanding

arXiv:2608.19059v1 Announce Type: cross Abstract: Long-term robot operation in evolving environments requires object-level understanding that persists across repeated revisits. Existing systems either

safetyarxiv-cs-cv

LumiTokens: 3D Relighting via Token-Space Lighting Transformation

arXiv:2608.18215v1 Announce Type: new Abstract: Existing 3D relighting methods operate through either explicit material decomposition, diffusion-based view-space generation, or a combination of both,

researcharxiv-cs-cv

Many Optimizers But Only One Training Path: Repeated Resampling for Adaptive Optimizer Selection

arXiv:2608.18810v1 Announce Type: new Abstract: An optimizer is usually chosen before training a deep neural network and then kept fixed. Treating optimizer choice as a hyperparameter could boost perf

Tutorials

MARCUS: Missing-Aware Region Representation with Contextual Urban Signals for Rent Prediction

arXiv:2608.18546v1 Announce Type: new Abstract: Multimodal urban data has expanded the applications of urban region representation learning, such as functional zone identification and real estate appr

tutorialsarxiv-cs-lg

MAVEN: A Macro-Societal Value Evaluation Framework of Multimodal Content with Compact Aligned Evaluators

arXiv:2608.18096v1 Announce Type: new Abstract: Assessing whether multimodal content aligns with macro-societal values, such as peace, justice, and freedom, has become an increasingly urgent challenge

Measuring the Partial-Credit Gap: A Strict Benchmark on Vietnam's 2025 Convex Marking Scheme

arXiv:2608.18336v1 Announce Type: new Abstract: When evaluating language models on human exams, benchmarks typically score each response as right or wrong and report the overall accuracy. This approac

Mechanistic Interpretability of Structure-Aware Numerical Reasoning in LLaMA 3.1 8B

arXiv:2608.18419v1 Announce Type: cross Abstract: Recent work has shown that large language models (LLMs) exhibit strong numerical sequence modeling capabilities and show promise in time-series predic

MedUAG: Unified Understanding and Generation for Medical Multimodal Models

arXiv:2608.18937v1 Announce Type: cross Abstract: Recent Multimodal Large Language Models (MLLMs) are rapidly evolving into unified understanding and generation (UAG) frameworks. However, extending th

MemFuse: Multi-Source Memory Fusion from Fragmented Observations

arXiv:2608.18704v1 Announce Type: cross Abstract: Long-term memory is essential for agents that operate across extended interactions, yet existing memory systems and benchmarks predominantly focus on

Metrics That Write Themselves: Evolving an Evaluator from Its Own Blind Spots

arXiv:2608.18744v1 Announce Type: new Abstract: Agents improve quickly against a reliable automatic metric and stall without one, and the applications that need them most, report generation among them