Search: “model-releases”

Breaking the Generator Barrier: Disentangled Representation for Generalizable AI-Text Detection

arXiv:2604.13692v1 Announce Type: new Abstract: As large language models (LLMs) generate text that increasingly resembles human writing, the subtle cues that distinguish AI-generated content from huma

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Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensus

DGX agent

arXiv:2604.13472v1 Announce Type: new Abstract: Cooperative multi-agent reinforcement learning (MARL) is widely used to address large joint observation and action spaces by decomposing a centralized c

model-releasesarxiv-cs-lg

16 Apr 2026

Can Large Language Models Reliably Extract Physiology Index Values from Coronary Angiography Reports?

arXiv:2604.13077v1 Announce Type: new Abstract: Coronary angiography (CAG) reports contain clinically relevant physiological measurements, yet this information is typically in the form of unstructured

CANVAS: Continuity-Aware Narratives via Visual Agentic Storyboarding

arXiv:2604.13452v1 Announce Type: new Abstract: Long-form visual storytelling requires maintaining continuity across shots, including consistent characters, stable environments, and smooth scene trans

Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning

arXiv:2604.13504v1 Announce Type: cross Abstract: Designing effective reward functions is a cornerstone of reinforcement learning (RL), yet it remains a challenging and labor-intensive process due to

CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation

arXiv:2504.21751v4 Announce Type: replace-cross Abstract: Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components

Coherence in the brain unfolds across separable temporal regimes

arXiv:2512.20481v4 Announce Type: replace-cross Abstract: To maintain coherence in language, the brain must satisfy key competing temporal demands: the gradual accumulation of meaning across extended

CollabCoder: Plan-Code Co-Evolution via Collaborative Decision-Making for Efficient Code Generation

arXiv:2604.13946v1 Announce Type: cross Abstract: Automated code generation remains a persistent challenge in software engineering, as conventional multi-agent frameworks are often constrained by stat

Common to Whom? Regional Cultural Commonsense and LLM Bias in India

arXiv:2601.15550v3 Announce Type: replace Abstract: Existing cultural commonsense benchmarks treat nations as monolithic, assuming uniform practices within national boundaries. But does cultural commo

Correct Chains, Wrong Answers: Dissociating Reasoning from Output in LLM Logic

arXiv:2604.13065v1 Announce Type: new Abstract: LLMs can execute every step of chain-of-thought reasoning correctly and still produce wrong final answers. We introduce the Novel Operator Test, a bench

Correct Prediction, Wrong Steps? Consensus Reasoning Knowledge Graph for Robust Chain-of-Thought Synthesis

arXiv:2604.14121v1 Announce Type: new Abstract: LLM reasoning traces suffer from complex flaws -- *Step Internal Flaws* (logical errors, hallucinations, etc.) and *Step-wise Flaws* (overthinking, unde

Counterfactual Peptide Editing for Causal TCR--pMHC Binding Inference

arXiv:2604.13256v1 Announce Type: new Abstract: Neural models for TCR-pMHC binding prediction are susceptible to shortcut learning: they exploit spurious correlations in training data -- such as pepti

Covariance-adapting algorithm for semi-bandits with application to sparse rewards

arXiv:2604.13738v1 Announce Type: cross Abstract: We investigate stochastic combinatorial semi-bandits, where the entire joint distribution of outcomes impacts the complexity of the problem instance (

Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions

arXiv:2405.19088v3 Announce Type: replace Abstract: Recent advancements in large multimodal language models have demonstrated remarkable proficiency across a wide range of tasks. Yet, these models sti

Data-driven Learning of Probabilistic Model of Binary Droplet Collision for Spray Simulation

arXiv:2604.13594v1 Announce Type: cross Abstract: Binary droplet collisions are ubiquitous in dense sprays. Traditional deterministic models cannot adequately represent transitional and stochastic beh

Decoding the Delta: Unifying Remote Sensing Change Detection and Understanding with Multimodal Large Language Models

arXiv:2604.14044v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general vision-language tasks, their application to remote sensing change understanding is hinde

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

Dental-TriageBench: Benchmarking Multimodal Reasoning for Hierarchical Dental Triage

arXiv:2604.13060v1 Announce Type: new Abstract: Dental triage is a safety-critical clinical routing task that requires integrating multimodal clinical information (e.g., patient complaints and radiogr

Design Space Exploration of Hybrid Quantum Neural Networks for Chronic Kidney Disease

arXiv:2604.13608v1 Announce Type: new Abstract: Hybrid Quantum Neural Networks (HQNNs) have recently emerged as a promising paradigm for near-term quantum machine learning. However, their practical pe

DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis

arXiv:2604.13416v1 Announce Type: new Abstract: Advances in radiance fields have enabled photorealistic novel view synthesis. In several domains, large-scale real-world datasets have been developed to

Do We Still Need Humans in the Loop? Comparing Human and LLM Annotation in Active Learning for Hostility Detection

arXiv:2604.13899v1 Announce Type: new Abstract: Instruction-tuned LLMs can annotate thousands of instances from a short prompt at negligible cost. This raises two questions for active learning (AL): c

Document-tuning for robust alignment to animals

arXiv:2604.13076v1 Announce Type: new Abstract: We investigate the robustness of value alignment via finetuning with synthetic documents, using animal compassion as a value that is both important in i

Drowsiness-Aware Adaptive Autonomous Braking System based on Deep Reinforcement Learning for Enhanced Road Safety

arXiv:2604.13878v1 Announce Type: new Abstract: Driver drowsiness significantly impairs the ability to accurately judge safe braking distances and is estimated to contribute to 10%-20% of road acciden

Efficient Multi-View 3D Object Detection by Dynamic Token Selection and Fine-Tuning

arXiv:2604.13586v1 Announce Type: new Abstract: Existing multi-view three-dimensional (3D) object detection approaches widely adopt large-scale pre-trained vision transformer (ViT)-based foundation mo

EmbodiedClaw: Conversational Workflow Execution for Embodied AI Development

model-releasesarxiv-cs-ro

arXiv:2604.13800v1 Announce Type: new Abstract: Embodied AI research is increasingly moving beyond single-task, single-environment policy learning toward multi-task, multi-scene, and multi-model setti

EMGFlow: Robust and Efficient Surface Electromyography Synthesis via Flow Matching

arXiv:2604.13685v1 Announce Type: cross Abstract: Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. Whi

Enhancing Confidence Estimation in Telco LLMs via Twin-Pass CoT-Ensembling

arXiv:2604.13271v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied to complex telecommunications tasks, including 3GPP specification analysis and O-RAN network troub

ESCAPE: Episodic Spatial Memory and Adaptive Execution Policy for Long-Horizon Mobile Manipulation

arXiv:2604.13633v1 Announce Type: new Abstract: Coordinating navigation and manipulation with robust performance is essential for embodied AI in complex indoor environments. However, as tasks extend o

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

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

Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection

arXiv:2604.13882v1 Announce Type: new Abstract: The evaluation of supervised machine learning models is a critical stage in the development of reliable predictive systems. Despite the widespread avail

Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detection

arXiv:2604.13232v1 Announce Type: new Abstract: This discussion paper re-examines SemEval-2020 Task 1, the most influential shared benchmark for lexical semantic change detection, through a three-part

Evaluating the Formal Reasoning Capabilities of Large Language Models through Chomsky Hierarchy

arXiv:2604.02709v2 Announce Type: replace Abstract: The formal reasoning capabilities of LLMs are crucial for advancing automated software engineering. However, existing benchmarks for LLMs lack syste

EVE: A Domain-Specific LLM Framework for Earth Intelligence

arXiv:2604.13071v1 Announce Type: new Abstract: We introduce Earth Virtual Expert (EVE), the first open-source, end-to-end initiative for developing and deploying domain-specialized LLMs for Earth Int

Exposia: Teaching and Assessment of Academic Writing Skills for Research Project Proposals and Peer Feedback

arXiv:2601.06536v2 Announce Type: replace Abstract: We present Exposia, the first public dataset that connects writing and feedback in higher education, enabling research on educationally grounded com

ExpSeek: Self-Triggered Experience Seeking for Web Agents

arXiv:2601.08605v2 Announce Type: replace Abstract: Experience intervention in web agents emerges as a promising technical paradigm, enhancing agent interaction capabilities by providing valuable insi

F-Actor: Controllable Conversational Behaviour in Full-Duplex Models

arXiv:2601.11329v3 Announce Type: replace Abstract: Spoken conversational systems require more than accurate speech generation to have human-like conversations: to feel natural and engaging, they must

Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions

arXiv:2509.18847v3 Announce Type: replace-cross Abstract: Tool-augmented large language models (LLMs) are usually trained with supervised imitation or coarse-grained reinforcement learning that optimi

Fast training of accurate physics-informed neural networks without gradient descent

arXiv:2405.20836v3 Announce Type: replace-cross Abstract: Solving time-dependent Partial Differential Equations (PDEs) is one of the most critical problems in computational science. While Physics-Info

FieldWorkArena: Agentic AI Benchmark for Real Field Work Tasks

arXiv:2505.19662v3 Announce Type: replace-cross Abstract: This paper introduces FieldWorkArena, a benchmark for agentic AI targeting real-world field work. With the recent increase in demand for agent

FiLM-Nav: Efficient and Generalizable Navigation via VLM Fine-tuning

model-releasesarxiv-cs-ro

arXiv:2509.16445v2 Announce Type: replace Abstract: Enabling robotic assistants to navigate complex environments and locate objects described in free-form language is a critical capability for real-wo

FlexGuard: Continuous Risk Scoring for Strictness-Adaptive LLM Content Moderation

arXiv:2602.23636v3 Announce Type: replace Abstract: Ensuring the safety of LLM-generated content is essential for real-world deployment. Most existing guardrail models formulate moderation as a fixed

Flow-based Generative Modeling of Potential Outcomes and Counterfactuals

arXiv:2505.16051v4 Announce Type: replace-cross Abstract: Predicting potential and counterfactual outcomes from observational data is central to individualized decision-making, particularly in clinica

fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding

arXiv:2511.21760v3 Announce Type: replace Abstract: Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capabi

Free Geometry: Refining 3D Reconstruction from Longer Versions of Itself

arXiv:2604.14048v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models are efficient but rigid: once trained, they perform inference in a zero-shot manner and cannot adapt to the test s

From Feelings to Metrics: Understanding and Formalizing How Users Vibe-Test LLMs

arXiv:2604.14137v1 Announce Type: new Abstract: Evaluating LLMs is challenging, as benchmark scores often fail to capture models' real-world usefulness. Instead, users often rely on ``vibe-testing'':

From Plausibility to Verifiability: Risk-Controlled Generative OCR with Vision-Language Models

arXiv:2603.19790v3 Announce Type: replace Abstract: Modern vision-language models (VLMs) can act as generative OCR engines, yet open-ended decoding can expose rare but consequential failures. We ident

From Weights to Activations: Is Steering the Next Frontier of Adaptation?

arXiv:2604.14090v1 Announce Type: new Abstract: Post-training adaptation of language models is commonly achieved through parameter updates or input-based methods such as fine-tuning, parameter-efficie

Functional Emotions or Situational Contexts? A Discriminating Test from the Mythos Preview System Card

arXiv:2604.13466v1 Announce Type: cross Abstract: The Claude Mythos Preview system card deploys emotion vectors, sparse autoencoder (SAE) features, and activation verbalisers to study model internals