Search: “gpt”

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

5 May 2026

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Model Releases

Perturbation Dose Responses in Recursive LLM Loops: Raw Switching, Stochastic Floors, and Persistent Escape under Append, Replace, and Dialog Updates

DGX agent

arXiv:2605.02236v1 Announce Type: cross Abstract: Recursive language-model loops often settle into recognizable attractor-like patterns. The practical question is how much injected text is needed to m

model-releasesarxiv-cs-cl

5 May 2026

Probe-Geometry Alignment: Erasing the Cross-Sequence Memorization Signature Below Chance

arXiv:2605.01699v1 Announce Type: new Abstract: Recent attacks show that behavioural unlearning of large language models leaves internal traces recoverable by adversarial probes. We characterise where

5 May 2026

AgentFloor: How Far Up the tool use Ladder Can Small Open-Weight Models Go?

arXiv:2605.00334v1 Announce Type: cross Abstract: Production agentic systems make many model calls per user request, and most of those calls are short, structured, and routine. This raises a practical

4 May 2026

Evaluating the Architectural Reasoning Capabilities of LLM Provers via the Obfuscated Natural Number Game

arXiv:2605.00677v1 Announce Type: new Abstract: While Large Language Models have achieved notable success on formal mathematics benchmarks such as MiniF2F, it remains unclear whether these results ste

4 May 2026

Auditing Frontier Vision-Language Models for Trustworthy Medical VQA: Grounding Failures, Format Collapse, and Domain Adaptation

arXiv:2604.27720v1 Announce Type: new Abstract: Deploying vision-language models (VLMs) in clinical settings demands auditable behavior under realistic failure conditions, yet the failure landscape of

1 May 2026

HealthBench Professional: Evaluating Large Language Models on Real Clinician Chats

arXiv:2604.27470v1 Announce Type: new Abstract: Millions of clinicians use ChatGPT to support clinical care, but evaluations of the most common use cases in model-clinician conversations are limited.

1 May 2026

Frontier Coding Agents Can Now Implement an AlphaZero Self-Play Machine Learning Pipeline For Connect Four That Performs Comparably to an External Solver

arXiv:2604.25067v1 Announce Type: cross Abstract: Forecasting when AI systems will become capable of meaningfully accelerating AI research is a central challenge for AI safety. Existing benchmarks mea

29 Apr 2026

MGSM-Pro: A Simple Strategy for Robust Multilingual Mathematical Reasoning Evaluation

arXiv:2601.21225v2 Announce Type: replace Abstract: Large language models have made substantial progress in mathematical reasoning. However, benchmark development for multilingual evaluation has lagge

29 Apr 2026

One Perturbation, Two Failure Modes: Probing VLM Safety via Embedding-Guided Typographic Perturbations

model-releasesarxiv-cs-cv

arXiv:2604.25102v1 Announce Type: new Abstract: Typographic prompt injection exploits vision language models' (VLMs) ability to read text rendered in images, posing a growing threat as VLMs power auto

29 Apr 2026

Channel Adaptation for EEG Foundation Models: A Systematic Benchmark Across Architectures, Tasks, and Training Regimes

arXiv:2604.23091v1 Announce Type: new Abstract: Scaling EEG foundation models requires pooling data across heterogeneous electrode montages, a prerequisite both for larger pretraining corpora and for

Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards

arXiv:2604.23341v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) as assistants in electric grid operations promises to streamline compliance and decision-making but exp

Research

Indirect Question Answering in English, German and Bavarian: A Challenging Task for High- and Low-Resource Languages Alike

arXiv:2603.15130v2 Announce Type: replace Abstract: Indirectness is a common feature of daily communication, yet is underexplored in NLP research for both low-resource as well as high-resource languag

researcharxiv-cs-cl

Jailbreaking Frontier Foundation Models Through Intention Deception

arXiv:2604.24082v1 Announce Type: cross Abstract: Large (vision-)language models exhibit remarkable capability but remain highly susceptible to jailbreaking. Existing safety training approaches aim to

Safety

MERIT: Modular Framework for Multimodal Misinformation Detection with Web-Grounded Reasoning

arXiv:2510.17590v2 Announce Type: replace Abstract: We present MERIT, an inference-time modular framework for multimodal misinformation detection that decomposes verification into four specialized mod

safetyarxiv-cs-ai

MTRouter: Cost-Aware Multi-Turn LLM Routing with History-Model Joint Embeddings

arXiv:2604.23530v1 Announce Type: cross Abstract: Multi-turn, long-horizon tasks are increasingly common for large language models (LLMs), but solving them typically requires many sequential model inv

Agents

PARASITE: Conditional System Prompt Poisoning to Hijack LLMs

arXiv:2505.16888v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed via third-party system prompts downloaded from public marketplaces. We identify a criti

agentsarxiv-cs-ai

Research

The Spectral Lifecycle of Transformer Training: Transient Compression Waves, Persistent Spectral Gradients, and the Q/K--V Asymmetry

arXiv:2604.22778v1 Announce Type: cross Abstract: We present the first systematic study of weight matrix singular value spectra during transformer pretraining, tracking full SVD decompositions of ever

researcharxiv-cs-ai

The Surprising Effectiveness of Membership Inference with Simple N-Gram Coverage

arXiv:2508.09603v2 Announce Type: replace Abstract: Membership inference attacks serves as useful tool for fair use of language models, such as detecting potential copyright infringement and auditing

Understanding the Limits of Automated Evaluation for Code Review Bots in Practice

arXiv:2604.24525v1 Announce Type: cross Abstract: Automated code review (ACR) bots are increasingly used in industrial software development to assist developers during pull request (PR) review. As ado

When Does Removing LayerNorm Help? Activation Bounding as a Regime-Dependent Implicit Regularizer

arXiv:2604.23434v1 Announce Type: cross Abstract: Dynamic Tanh (DyT) removes LayerNorm by bounding activations with a learned tanh(alpha x). We show that this bounding is a regime-dependent implicit r

CharTide: Data-Centric Chart-to-Code Generation via Tri-Perspective Tuning and Inquiry-Driven Evolution

model-releasesarxiv-cs-cv

arXiv:2604.22192v1 Announce Type: new Abstract: Chart-to-code generation demands strict visual precision and syntactic correctness from Vision-Language Models (VLMs). However, existing approaches are

Test-Time Matching: Unlocking Compositional Reasoning in Multimodal Models

arXiv:2510.07632v2 Announce Type: replace Abstract: Frontier AI models have achieved remarkable progress, yet recent studies suggest they struggle with compositional reasoning, often performing at or

UR^2: Unify RAG and Reasoning through Reinforcement Learning

arXiv:2508.06165v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown strong capabilities through two complementary paradigms: Retrieval-Augmented Generation (RAG) for know

When Does LLM Self-Correction Help? A Control-Theoretic Markov Diagnostic and Verify-First Intervention

arXiv:2604.22273v1 Announce Type: new Abstract: Iterative self-correction is widely used in agentic LLM systems, but when repeated refinement helps versus hurts remains unclear. We frame self-correcti

Process Supervision via Verbal Critique Improves Reasoning in Large Language Models

arXiv:2604.21611v1 Announce Type: cross Abstract: Inference-time scaling for LLM reasoning has focused on three axes: chain depth, sample breadth, and learned step-scorers (PRMs). We introduce a fourt

24 Apr 2026

Can 'AI' Be a Doctor? A Study of Empathy, Readability, and Alignment in Clinical LLMs

arXiv:2604.20791v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in healthcare, yet their communicative alignment with clinical standards remains insufficiently

23 Apr 2026

Exploring Data Augmentation and Resampling Strategies for Transformer-Based Models to Address Class Imbalance in AI Scoring of Scientific Explanations in NGSS Classroom

arXiv:2604.19754v1 Announce Type: new Abstract: Automated scoring of students' scientific explanations offers the potential for immediate, accurate feedback, yet class imbalance in rubric categories p

23 Apr 2026

Infection-Reasoner: A Compact Vision-Language Model for Wound Infection Classification with Evidence-Grounded Clinical Reasoning

arXiv:2604.19937v1 Announce Type: cross Abstract: Assessing chronic wound infection from photographs is challenging because visual appearance varies across wound etiologies, anatomical locations, and

23 Apr 2026

CounterRefine: Answer-Conditioned Counterevidence Retrieval for Inference-Time Knowledge Repair in Factual Question Answering

arXiv:2603.16091v2 Announce Type: replace-cross Abstract: In factual question answering, many errors are not failures of access but failures of commitment: the system retrieves relevant evidence, yet

Do LLMs Game Formalization? Evaluating Faithfulness in Logical Reasoning

arXiv:2604.19459v1 Announce Type: new Abstract: Formal verification guarantees proof validity but not formalization faithfulness. For natural-language logical reasoning, where models construct axiom s

LegalBench-BR: A Benchmark for Evaluating Large Language Models on Brazilian Legal Decision Classification

arXiv:2604.18878v1 Announce Type: new Abstract: We introduce LegalBench-BR, the first public benchmark for evaluating language models on Brazilian legal text classification. The dataset comprises 3,10

Less Is More: Cognitive Load and the Single-Prompt Ceiling in LLM Mathematical Reasoning

arXiv:2604.18897v1 Announce Type: new Abstract: We present a systematic empirical study of prompt engineering for formal mathematical reasoning in the context of the SAIR Equational Theories Stage 1 c

ReflectMT: Internalizing Reflection for Efficient and High-Quality Machine Translation

arXiv:2604.19144v1 Announce Type: new Abstract: Recent years have witnessed growing interest in applying Large Reasoning Models (LRMs) to Machine Translation (MT). Existing approaches predominantly ad

Regression with Large Language Models for Materials and Molecular Property Prediction

arXiv:2409.06080v2 Announce Type: replace-cross Abstract: We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviatio

Applications

Seeing Candidates at Scale: Multimodal LLMs for Visual Political Communication on Instagram

arXiv:2604.19489v1 Announce Type: new Abstract: This paper presents a computational case study that evaluates the capabilities of specialized machine learning models and emerging multimodal large lang

applicationsarxiv-cs-cv

Safety

ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioning

arXiv:2603.29068v3 Announce Type: replace Abstract: This paper presents ARCS (Autoregressive Circuit Synthesis), a system for amortized analog circuit generation. ARCS produces complete, SPICE-simulat

safetyarxiv-cs-lg

21 Apr 2026

Budget-Aware Anytime Reasoning with LLM-Synthesized Preference Data

arXiv:2601.11038v2 Announce Type: replace Abstract: We study the reasoning behavior of large language models (LLMs) under limited computation budgets. In such settings, producing useful partial soluti

21 Apr 2026

Harness as an Asset: Enforcing Determinism via the Convergent AI Agent Framework (CAAF)

arXiv:2604.17025v1 Announce Type: cross Abstract: Large Language Models (LLMs) produce a controllability gap in safety-critical engineering: even low rates of undetected constraint violations render a

21 Apr 2026

No Universal Courtesy: A Cross-Linguistic, Multi-Model Study of Politeness Effects on LLMs Using the PLUM Corpus

arXiv:2604.16275v1 Announce Type: new Abstract: This paper explores the response of Large Language Models (LLMs) to user prompts with different degrees of politeness and impoliteness. The Politeness T

20 Apr 2026

Research

Hierarchical Semantic Retrieval with Cobweb

arXiv:2510.02539v2 Announce Type: replace Abstract: Neural document retrieval often treats a corpus as a flat cloud of vectors scored at a single granularity, leaving corpus structure underused and ex

researcharxiv-cs-cl

Pangu-ACE: Adaptive Cascaded Experts for Educational Response Generation on EduBench

arXiv:2604.14828v1 Announce Type: new Abstract: Educational assistants should spend more computation only when the task needs it. This paper rewrites our earlier draft around the system that was actua

ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents

arXiv:2604.14261v1 Announce Type: new Abstract: The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-base

Applications

Text2Arch: A Dataset for Generating Scientific Architecture Diagrams from Natural Language Descriptions

arXiv:2604.14941v1 Announce Type: new Abstract: Communicating complex system designs or scientific processes through text alone is inefficient and prone to ambiguity. A system that automatically gener

applicationsarxiv-cs-cl

Theory of Mind in Action: The Instruction Inference Task in Dynamic Human-Agent Collaboration

arXiv:2507.02935v2 Announce Type: replace Abstract: Successful human-agent teaming relies on an agent being able to understand instructions given by a (human) principal. In many cases, an instruction

Agents

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods

arXiv:2603.21011v2 Announce Type: replace-cross Abstract: Finite element (FE) analysis guides the design and verification of nearly all manufactured objects. It is at the core of computational enginee

agentsarxiv-cs-ai

15 Apr 2026

Is Vibe Coding the Future? An Empirical Assessment of LLM Generated Codes for Construction Safety

arXiv:2604.12311v1 Announce Type: cross Abstract: The emergence of vibe coding, a paradigm where non-technical users instruct Large Language Models (LLMs) to generate executable codes via natural lang

15 Apr 2026

KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning

arXiv:2603.21440v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate impressive natural language capabilities but often struggle with knowledge-intensive reasoning tasks.