Search: “open-weights”

arXiv:2605.06761v1 Announce Type: new Abstract: The web is complex, open-ended, and constantly changing, making it challenging to scale training data for visual web agents. Existing data collection at

applicationsarxiv-cs-ai

11 May 2026

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Model Releases

MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents

DGX agent

arXiv:2605.03952v1 Announce Type: cross Abstract: Coding agents often pass per-prompt safety review yet ship exploitable code when their tasks are decomposed into routine engineering tickets. The chal

model-releasesarxiv-cs-ai

7 May 2026

Self-Prompting Small Language Models for Privacy-Sensitive Clinical Information Extraction

arXiv:2605.04221v1 Announce Type: new Abstract: Clinical named entity recognition from dental progress notes is challenging because documentation is highly unstructured, domain-specific, and often pri

7 May 2026

12 Angry AI Agents: Evaluating Multi-Agent LLM Decision-Making Through Cinematic Jury Deliberation

arXiv:2605.01986v1 Announce Type: new Abstract: What if the twelve jurors of Sidney Lumet's 12 Angry Men (1957) were not men, but large language models? Would the one juror who disagrees still be able

Code World Model Preparedness Report

arXiv:2605.00932v1 Announce Type: cross Abstract: This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conduc

researcharxiv-cs-ai

Local Ai

GISclaw: A Comprehensive Open-Source LLM Agent System for Realistic Multi-Step Geospatial Analysis

arXiv:2603.26845v2 Announce Type: replace-cross Abstract: Most LLM-driven GIS assistants solve narrow single-step tasks tightly coupled to proprietary platforms such as ArcGIS or QGIS, limiting their

local-aiarxiv-cs-ai

Tutorials

Natural Language Processing: A Comprehensive Practical Guide from Tokenisation to RLHF

arXiv:2605.03799v1 Announce Type: new Abstract: This preprint presents a systematic, research-oriented practicum that guides the reader through the entire modern NLP pipeline: from tokenisation and ve

tutorialsarxiv-cs-cl

Tutorials

Retrieving Floods without Floodlights: Topic Models as Binary Classifiers for Extreme Climate Events in German News

arXiv:2605.03450v1 Announce Type: new Abstract: In studies of media coverage of extreme climate events, NLP methods have become indispensable for identifying relevant texts in large news databases. St

tutorialsarxiv-cs-cl

Local Ai

SHIELD: A Diverse Clinical Note Dataset and Distilled Small Language Models for Enterprise-Scale De-identification

arXiv:2605.03301v1 Announce Type: new Abstract: De-identification of clinical text remains essential for secondary use of electronic health records (EHRs), yet public benchmarks such as i2b2 2006/2014

local-aiarxiv-cs-cl

CLaC at SemEval-2026 Task 6: Response Clarity Detection in Political Discourse

arXiv:2605.02170v1 Announce Type: new Abstract: In this paper, we present our system for SemEval-2026 Task 6 (CLARITY) on response clarity and evasion detection in question-answer pairs from U.S. pres

Decoding-Time Debiasing via Process Reward Models: From Controlled Fill-in to Open-Ended Generation

arXiv:2605.02348v1 Announce Type: new Abstract: Large language models pick up social biases from the data they are trained on and carry those biases into downstream applications, often reinforcing ste

HalluScan: A Systematic Benchmark for Detecting and Mitigating Hallucinations in Instruction-Following LLMs

arXiv:2605.02443v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse natural language processing tasks, yet they remain susceptible to

Hardware

Maistros: A Greek Large Language Model Adapted Through Knowledge Distillation From Large Reasoning Models

arXiv:2605.01870v1 Announce Type: new Abstract: Large Language Models (LLMs) have substantially advanced the field of Natural Language Processing (NLP), achieving state-of-the-art performance across a

hardwarearxiv-cs-cl

Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks

arXiv:2605.01417v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insuff

VideoNet: A Large-Scale Dataset for Domain-Specific Action Recognition

model-releasesarxiv-cs-cv

arXiv:2605.02834v1 Announce Type: new Abstract: Videos are unique in their ability to capture actions which transcend multiple frames. Accordingly, for many years action recognition was the quintessen

What Single-Prompt Accuracy Misses: A Multi-Variant Reliability Audit of Language Models

arXiv:2605.02038v1 Announce Type: new Abstract: Single-prompt accuracy is the dominant way to benchmark language models, but it can miss reliability failures that matter. We evaluate a 15-model open-w

Estimating LLM Grading Ability and Response Difficulty in Automatic Short Answer Grading via Item Response Theory

arXiv:2605.00238v1 Announce Type: new Abstract: Automated short answer grading (ASAG) with large language models (LLMs) is commonly evaluated with aggregate metrics such as macro-F1 and Cohen's kappa.

safetyarxiv-cs-cl

4 May 2026

Why Do LLMs Struggle in Strategic Play? Broken Links Between Observations, Beliefs, and Actions

arXiv:2605.00226v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly tasked with strategic decision-making under incomplete information, such as in negotiation and policymakin

4 May 2026

Models Recall What They Violate: Constraint Adherence in Multi-Turn LLM Ideation

arXiv:2604.28031v1 Announce Type: new Abstract: When researchers iteratively refine ideas with large language models, do the models preserve fidelity to the original objective? We introduce DriftBench

1 May 2026

ORFS-agent: Tool-Using Agents for Chip Design Optimization

arXiv:2506.08332v3 Announce Type: replace Abstract: Machine learning has been widely used to optimize complex engineering workflows across numerous domains. In integrated circuit design, modern flows

1 May 2026

Human-in-the-Loop Benchmarking of Heterogeneous LLMs for Automated Competency Assessment in Secondary Level Mathematics

arXiv:2604.26607v1 Announce Type: new Abstract: As Competency-Based Education (CBE) is gaining traction around the world, the shift from marks-based assessment to qualitative competency mapping is a m

30 Apr 2026

LIT-RAGBench: Benchmarking Generator Capabilities of Large Language Models in Retrieval-Augmented Generation

arXiv:2603.06198v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) is a framework in which a Generator, such as a Large Language Model (LLM), produces answers by retrieving docum

30 Apr 2026

Self-Jailbreaking: Language Models Can Reason Themselves Out of Safety Alignment After Benign Reasoning Training

arXiv:2510.20956v2 Announce Type: replace-cross Abstract: We discover a novel and surprising phenomenon of unintentional misalignment in reasoning language models (RLMs), which we call self-jailbreaki

30 Apr 2026

The Structured Output Benchmark: A Multi-Source Benchmark for Evaluating Structured Output Quality in Large Language Models

arXiv:2604.25359v1 Announce Type: new Abstract: Large Language Models are increasingly being deployed to extract structured data from unstructured and semi-structured sources: parsing invoices, medica

29 Apr 2026

Analytica: Soft Propositional Reasoning for Robust and Scalable LLM-Driven Analysis

arXiv:2604.23072v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly tasked with complex real-world analysis (e.g., in financial forecasting, scientific discovery), yet t

28 Apr 2026

Surface Sensitivity in Lean 4 Autoformalization

arXiv:2604.23135v1 Announce Type: new Abstract: Natural-language variation poses a key challenge in Lean autoformalization: semantically equivalent paraphrases of the same theorem statements can induc

researcharxiv-cs-lg

28 Apr 2026

Survey Response Generation: Generating Closed-Ended Survey Responses In-Silico with Large Language Models

arXiv:2510.11586v2 Announce Type: replace Abstract: Many in-silico simulations of human survey responses with large language models (LLMs) focus on generating closed-ended survey responses, whereas LL

safetyarxiv-cs-cl

27 Apr 2026

Dialect vs Demographics: Quantifying LLM Bias from Implicit Linguistic Signals vs. Explicit User Profiles

arXiv:2604.21152v1 Announce Type: cross Abstract: As state-of-the-art Large Language Models (LLMs) have become ubiquitous, ensuring equitable performance across diverse demographics is critical. Howev

From Codebooks to VLMs: Evaluating Automated Visual Discourse Analysis for Climate Change on Social Media

model-releasesarxiv-cs-cv

arXiv:2604.21786v1 Announce Type: new Abstract: Social media platforms have become primary arenas for climate communication, generating millions of images and posts that - if systematically analysed -

Preserving Decision Sovereignty in Military AI: A Trade-Secret-Safe Architectural Framework for Model Replaceability, Human Authority, and State Control

arXiv:2604.20867v1 Announce Type: cross Abstract: Recent events surrounding the relationship between frontier AI suppliers and national-security customers have made a structural problem newly visible:

Serialisation Strategy Matters: How FHIR Data Format Affects LLM Medication Reconciliation

arXiv:2604.21076v1 Announce Type: cross Abstract: Medication reconciliation at clinical handoffs is a high-stakes, error-prone process. Large language models are increasingly proposed to assist with t

Slot Machines: How LLMs Keep Track of Multiple Entities

arXiv:2604.21139v1 Announce Type: new Abstract: Language models must bind entities to the attributes they possess and maintain several such binding relationships within a context. We study how multipl

To See the Unseen: on the Generalization Ability of Transformers in Symbolic Reasoning

arXiv:2604.21632v1 Announce Type: new Abstract: We investigate the ability of decoder-only transformer models to perform abstract symbolic reasoning; specifically solving propositional logic reasoning

Cooperative Profiles Predict Multi-Agent LLM Team Performance in AI for Science Workflows

arXiv:2604.20658v1 Announce Type: new Abstract: Multi-agent systems built from teams of large language models (LLMs) are increasingly deployed for collaborative scientific reasoning and problem-solvin

DistortBench: Benchmarking Vision Language Models on Image Distortion Identification

arXiv:2604.19966v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used in settings where sensitivity to low-level image degradations matters, including content moderatio

Applications

Do Hallucination Neurons Generalize? Evidence from Cross-Domain Transfer in LLMs

arXiv:2604.19765v1 Announce Type: cross Abstract: Recent work identifies a sparse set of 'hallucination neurons' (H-neurons), less than 0.1% of feed-forward network neurons, that reliably predict when

applicationsarxiv-cs-ai

HumorRank: A Tournament-Based Leaderboard for Evaluating Humor Generation in Large Language Models

arXiv:2604.19786v1 Announce Type: new Abstract: Evaluating humor in large language models (LLMs) is an open challenge because existing approaches yield isolated, incomparable metrics rather than unifi

Tutorials

Render-in-the-Loop: Vector Graphics Generation via Visual Self-Feedback

arXiv:2604.20730v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown promising capabilities in generating Scalable Vector Graphics (SVG) via direct code synthesis. Howev

tutorialsarxiv-cs-cv

AlignCultura: Towards Culturally Aligned Large Language Models?

arXiv:2604.19016v1 Announce Type: new Abstract: Cultural alignment in Large Language Models (LLMs) is essential for producing contextually aware, respectful, and trustworthy outputs. Without it, model

Benchmarking Misuse Mitigation Against Covert Adversaries

arXiv:2506.06414v2 Announce Type: replace-cross Abstract: Existing language model safety evaluations focus on overt attacks and low-stakes tasks. In reality, an attacker can easily subvert existing sa

Capturing Classic Authorial Style in Long-Form Story Generation with GRPO Fine-Tuning

arXiv:2512.05747v3 Announce Type: replace Abstract: Evaluating and optimising authorial style in long-form story generation remains challenging because style is often assessed with ad hoc prompting an

safetyarxiv-cs-cl

LLM-as-Judge Framework for Evaluating Tone-Induced Hallucination in Vision-Language Models

arXiv:2604.18803v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed in settings where reliable visual grounding carries operational consequences, yet their behavi

LLMs Know They're Wrong and Agree Anyway: The Shared Sycophancy-Lying Circuit

arXiv:2604.19117v1 Announce Type: new Abstract: When a language model agrees with a user's false belief, is it failing to detect the error, or noticing and agreeing anyway? We show the latter. Across

safetyarxiv-cs-lg

Machine individuality: Separating genuine idiosyncrasy from response bias in large language models

arXiv:2604.16755v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly integrated into daily life, in roles ranging from high-stakes decision support to companionship, un

Applications

An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs

arXiv:2603.04545v2 Announce Type: replace Abstract: Efficient inference for graph neural networks (GNNs) on large knowledge graphs (KGs) is essential for many real-world applications. GNN inference qu

applicationsarxiv-cs-lg

BengaliMoralBench: A Benchmark for Auditing Moral Reasoning in Large Language Models within Bengali Language and Culture

arXiv:2511.03180v2 Announce Type: replace Abstract: As multilingual Large Language Models (LLMs) gain traction across South Asia, their alignment with local ethical norms, particularly for Bengali, sp

Countdown-Code: A Testbed for Studying The Emergence and Generalization of Reward Hacking in RLVR

arXiv:2603.07084v2 Announce Type: replace-cross Abstract: Reward hacking is a form of misalignment in which models overoptimize proxy rewards without genuinely solving the underlying task. Precisely m

Defragmenting Language Models: An Interpretability-based Approach for Vocabulary Expansion

arXiv:2604.16656v1 Announce Type: new Abstract: All languages are equal; when it comes to tokenization, some are more equal than others. Tokens are the hidden currency that dictate the cost and latenc