Search: “gemini”

DeEscalWild: A Real-World Benchmark for Automated De-Escalation Training with SLMs

arXiv:2604.13075v1 Announce Type: new Abstract: Effective de-escalation is critical for law enforcement safety and community trust, yet traditional training methods lack scalability and realism. While

16 Apr 2026

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Evaluating LLM-Based Translation of a Low-Resource Technical Language: The Medical and Philosophical Greek of Galen

DGX agent

arXiv:2602.24119v2 Announce Type: replace Abstract: Purpose: This study evaluates the quality of commercial large language model (LLM) machine translation (MT) for Ancient Greek technical prose and be

model-releasesarxiv-cs-cl

16 Apr 2026

LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning

model-releasesarxiv-cs-lg

arXiv:2604.14140v1 Announce Type: new Abstract: As language models are increasingly deployed for complex autonomous tasks, their ability to reason accurately over longer horizons becomes critical. An

16 Apr 2026

ROSE: Retrieval-Oriented Segmentation Enhancement

arXiv:2604.14147v1 Announce Type: new Abstract: Existing segmentation models based on multimodal large language models (MLLMs), such as LISA, often struggle with novel or emerging entities due to thei

16 Apr 2026

Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch

model-releasesarxiv-cs-lg

arXiv:2603.24647v4 Announce Type: replace Abstract: The autoresearch repository enables an LLM agent to optimize hyperparameters by editing training code directly. We use it as a testbed to compare cl

GoodPoint: Learning Constructive Scientific Paper Feedback from Author Responses

arXiv:2604.11924v1 Announce Type: new Abstract: While LLMs hold significant potential to transform scientific research, we advocate for their use to augment and empower researchers rather than to auto

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

LaV-CoT: Language-Aware Visual CoT with Multi-Aspect Reward Optimization for Real-World Multilingual VQA

arXiv:2509.10026v4 Announce Type: replace Abstract: As large vision language models (VLMs) advance, their capabilities in multilingual visual question answering (mVQA) have significantly improved. Cha

Leveraging Weighted Syntactic and Semantic Context Assessment Summary (wSSAS) Towards Text Categorization Using LLMs

arXiv:2604.12049v1 Announce Type: cross Abstract: The use of Large Language Models (LLMs) for reliable, enterprise-grade analytics such as text categorization is often hindered by the stochastic natur

LLM-Guided Prompt Evolution for Password Guessing

arXiv:2604.12601v1 Announce Type: cross Abstract: Passwords still remain a dominant authentication method, yet their security is routinely subverted by predictable user choices and large-scale credent

StoryScope: Investigating idiosyncrasies in AI fiction

arXiv:2604.03136v4 Announce Type: replace Abstract: As AI-generated fiction becomes increasingly prevalent, questions of authorship and originality are becoming central to how written work is evaluate

BareBones: Benchmarking Zero-Shot Geometric Comprehension in VLMs

arXiv:2604.10528v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) demonstrate remarkable zero-shot recognition capabilities across a diverse spectrum of multimodal tasks, it yet rema

Both Ends Count! Just How Good are LLM Agents at 'Text-to-Big SQL'?

arXiv:2602.21480v4 Announce Type: replace-cross Abstract: Text-to-SQL and Big Data are both extensively benchmarked fields, yet there is limited research that evaluates them jointly. In the real world

Comparative Analysis of Large Language Models in Healthcare

arXiv:2604.10316v1 Announce Type: new Abstract: Background: Large Language Models (LLMs) are transforming artificial intelligence applications in healthcare due to their ability to understand, generat

Consistency of AI-Generated Exercise Prescriptions: A Repeated Generation Study Using a Large Language Model

arXiv:2604.11287v1 Announce Type: new Abstract: Background: Large language models (LLMs) have been explored as tools for generating personalized exercise prescriptions, yet the consistency of outputs

DeepReviewer 2.0: A Traceable Agentic System for Auditable Scientific Peer Review

arXiv:2604.09590v1 Announce Type: new Abstract: Automated peer review is often framed as generating fluent critique, yet reviewers and area chairs need judgments they can audit: where a concern applie

EduIllustrate: Towards Scalable Automated Generation Of Multimodal Educational Content

arXiv:2604.05005v2 Announce Type: replace-cross Abstract: Large language models are increasingly used as educational assistants, yet evaluation of their educational capabilities remains concentrated o

Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning

arXiv:2604.11462v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle with long-horizon tasks due to the 'context bottleneck' and the 'lost-in-the-middle' phenomenon, where accumulated

GAMBIT: A Gamified Jailbreak Framework for Multimodal Large Language Models

arXiv:2601.03416v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have become widely deployed, yet their safety alignment remains fragile under adversarial inputs. Previous

General-purpose LLMs as Models of Human Driver Behavior: The Case of Simplified Merging

arXiv:2604.09609v1 Announce Type: new Abstract: Human behavior models are essential as behavior references and for simulating human agents in virtual safety assessment of automated vehicles (AVs), yet

GIANTS: Generative Insight Anticipation from Scientific Literature

arXiv:2604.09793v1 Announce Type: cross Abstract: Scientific breakthroughs often emerge from synthesizing prior ideas into novel contributions. While language models (LMs) show promise in scientific d

Hunt Globally: Wide Search AI Agents for Drug Asset Scouting in Investing, Business Development, and Competitive Intelligence

arXiv:2602.15019v3 Announce Type: replace Abstract: Bio-pharmaceutical innovation has shifted: many new drug assets now originate outside the United States and are disclosed primarily via regional, no

MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models

arXiv:2511.18373v2 Announce Type: replace Abstract: Vision Language Models (VLMs) perform well on standard video tasks but struggle with physics-related reasoning involving motion dynamics and spatial

Measuring and curing reasoning rigidity: from decorative chain-of-thought to genuine faithfulness

arXiv:2603.22816v3 Announce Type: replace-cross Abstract: Language models increasingly show their work by writing step-by-step reasoning before answering. But are these steps genuinely used, or is the

OmniScript: Towards Audio-Visual Script Generation for Long-Form Cinematic Video

arXiv:2604.11102v1 Announce Type: new Abstract: Current multimodal large language models (MLLMs) have demonstrated remarkable capabilities in short-form video understanding, yet translating long-form

RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time

arXiv:2604.11626v1 Announce Type: new Abstract: Most reward models for visual generation reduce rich human judgments to a single unexplained score, discarding the reasoning that underlies preference.

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

arXiv:2604.10916v1 Announce Type: cross Abstract: Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-language models (VLMs) could enable autonomous ultrasound

The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems

arXiv:2604.11309v1 Announce Type: cross Abstract: Large Language Models (LLMs) face prominent security risks from jailbreaking, a practice that manipulates models to bypass built-in security constrain

UniToolCall: Unifying Tool-Use Representation, Data, and Evaluation for LLM Agents

arXiv:2604.11557v1 Announce Type: new Abstract: Tool-use capability is a fundamental component of LLM agents, enabling them to interact with external systems through structured function calls. However

What Users Leave Unsaid: Under-Specified Queries Limit Vision-Language Models

arXiv:2601.06165v2 Announce Type: replace-cross Abstract: Current vision-language benchmarks predominantly feature well-structured questions with clear, explicit prompts. However, real user queries ar

Facet-Level Tracing of Evidence Uncertainty and Hallucination in RAG

arXiv:2604.09174v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) aims to reduce hallucination by grounding answers in retrieved evidence, yet hallucinated answers remain common eve

Lessons Without Borders? Evaluating Cultural Alignment of LLMs Using Multilingual Story Moral Generation

arXiv:2604.08797v1 Announce Type: cross Abstract: Stories are key to transmitting values across cultures, but their interpretation varies across linguistic and cultural contexts. Thus, we introduce mu

Neural networks for Text-to-Speech evaluation

arXiv:2604.08562v1 Announce Type: cross Abstract: Ensuring that Text-to-Speech (TTS) systems deliver human-perceived quality at scale is a central challenge for modern speech technologies. Human subje

SenBen: Sensitive Scene Graphs for Explainable Content Moderation

arXiv:2604.08819v1 Announce Type: cross Abstract: Content moderation systems classify images as safe or unsafe but lack spatial grounding and interpretability: they cannot explain what sensitive behav

Towards Knowledgeable Deep Research: Framework and Benchmark

arXiv:2604.07720v2 Announce Type: replace Abstract: Deep Research (DR) requires LLM agents to autonomously perform multi-step information seeking, processing, and reasoning to generate comprehensive r

Action Without Interaction: Probing the Physical Foundations of Video LMMs via Contact-Release Detection

arXiv:2511.20162v2 Announce Type: replace Abstract: Large multi-modal models (LMMs) show increasing performance in realistic visual tasks for images and, more recently, for videos. For example, given

An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applications

arXiv:2306.02781v4 Announce Type: replace-cross Abstract: Generative artificial intelligence, and large language models in particular, have emerged as one of the most transformative paradigms in moder

Break Me If You Can: Self-Jailbreaking of Aligned LLMs via Lexical Insertion Prompting

arXiv:2601.02670v2 Announce Type: replace Abstract: We introduce self-jailbreaking, a threat model in which an aligned LLM guides its own compromise. Unlike most jailbreak techniques, which oft

Broken by Default: A Formal Verification Study of Security Vulnerabilities in AI-Generated Code

arXiv:2604.05292v2 Announce Type: replace-cross Abstract: AI coding assistants are now used to generate production code in security-sensitive domains, yet the exploitability of their outputs remains u

Can Vision Language Models Judge Action Quality? An Empirical Evaluation

arXiv:2604.08294v1 Announce Type: cross Abstract: Action Quality Assessment (AQA) has broad applications in physical therapy, sports coaching, and competitive judging. Although Vision Language Models

Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection

arXiv:2506.19420v2 Announce Type: replace Abstract: Multimodal sarcasm understanding is a high-order cognitive task. Although large language models (LLMs) have shown impressive performance on many dow

HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents

arXiv:2604.07430v1 Announce Type: new Abstract: We introduce HY-Embodied-0.5, a family of foundation models specifically designed for real-world embodied agents. To bridge the gap between general Visi

Small Vision-Language Models are Smart Compressors for Long Video Understanding

arXiv:2604.08120v1 Announce Type: cross Abstract: Adapting Multimodal Large Language Models (MLLMs) for hour-long videos is bottlenecked by context limits. Dense visual streams saturate token budgets

Strategic Persuasion with Trait-Conditioned Multi-Agent Systems for Iterative Legal Argumentation

arXiv:2604.07028v1 Announce Type: cross Abstract: Strategic interaction in adversarial domains such as law, diplomacy, and negotiation is mediated by language, yet most game-theoretic models abstract

The AI Skills Shift: Mapping Skill Obsolescence, Emergence, and Transition Pathways in the LLM Era

arXiv:2604.06906v1 Announce Type: cross Abstract: As Large Language Models reshape the global labor market, policymakers and workers need empirical data on which occupational skills may be most suscep