Search: “model-releases”

Automated Generation of Complexity-Validated Decision Scenarios Using Large Language Models

arXiv:2608.08822v1 Announce Type: new Abstract: Cognitive decision-making research depends on diverse scenarios with carefully controlled complexity, yet manual production is slow, inconsistent, and b

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Automating Deception: Scalable Multi-Turn LLM Jailbreaks

DGX agent

arXiv:2511.19517v3 Announce Type: replace-cross Abstract: Multi-turn conversational attacks, which leverage psychological principles like Foot-in-the-Door (FITD), where a small initial request paves t

model-releasesarxiv-cs-ai

11 Aug 2026

AutoRefine: Compiling Trajectories into Validated Typed Agent Artifacts

arXiv:2601.22758v2 Announce Type: replace Abstract: Large language model agents repeatedly encounter related tasks, yet systems that learn from trajectories commit every lesson to one predefined artif

Autorubric: A Unifying Framework for Rubric-Based LLM Evaluation on Non-Verifiable Tasks

arXiv:2603.00077v3 Announce Type: replace-cross Abstract: Rubric-based LLM judges have become indispensable for evaluating and optimizing systems on non-verifiable tasks, where success cannot be reduc

Avalon-ToM-Bench: Evaluating Fine-Grained Theory of Mind via Asymmetric Game Mechanics

arXiv:2608.09638v1 Announce Type: new Abstract: Theory of Mind (ToM) is essential for agent interactions, yet existing evaluations either rely on static scenarios that oversimplify mental-state reason

Back to the Future: A workbook time machine for spread sheet creation benchmarks

arXiv:2608.07873v1 Announce Type: new Abstract: We introduce the workbook time machine, a pipeline that automatically creates benchmarks evaluating the ability of language models to create derived obj

BAG: Budget-Aware Gating for Diffusion Caching

arXiv:2608.09231v1 Announce Type: new Abstract: Diffusion caching is a lightweight strategy that accelerates Diffusion Transformers (DiTs) by reusing intermediate features across denoising steps, but

BAP-MOS: Bandit-Based Adaptive Prompting for Boundary-Sensitive Multi-Organ Segmentation

arXiv:2608.08191v1 Announce Type: new Abstract: Multi-organ ultrasound segmentation remains challenging when anatomically adjacent structures must be delineated jointly, as localized boundary errors c

Bayesian Symbolic Regression with Entropic Reinforcement Learning

arXiv:2608.09617v1 Announce Type: new Abstract: Symbolic regression is the problem of finding an algebraic expression describing a stochastic dependence of a target variable on a set of inputs. Unlike

BDH-CQ: In-Context Learning with Recurrent Latent Reasoning

arXiv:2608.09888v1 Announce Type: cross Abstract: We introduce BDH-CQ, a reasoning model that combines in-context learning with recurrent latent reasoning. Inputs presented at inference time continuou

Benchmarking In-context Experiential Learning Through Repeated Product Recommendations

arXiv:2511.22130v2 Announce Type: replace Abstract: To navigate ever-shifting real-world environments, agents must grapple with incomplete knowledge and adapt their strategies through experience. Howe

Benchmarking the Robustness of Agentic Systems to Adversarially-Induced Harms

arXiv:2508.16481v3 Announce Type: replace Abstract: Ensuring the safe use of agentic systems requires a thorough understanding of the range of malicious behaviors these systems may exhibit. In this pa

Beyond Direct Identifiers: Probabilistic Privacy Risk Estimation for Privacy-Conscious LLM Query Delegation

arXiv:2608.09140v1 Announce Type: cross Abstract: Recent work on protecting privacy during user-LLM interactions often focuses on direct, explicit identifiers: the personally-identifiable information

Beyond Naturalness: Probing Automated Text-To-Speech Evaluators on Linguistically Grounded Dimensions

arXiv:2608.09930v1 Announce Type: cross Abstract: Automated Text-to-Speech (TTS) evaluation methods (Mean Opinion Score (MOS) predictors and Audio Large Language Models (Audio-LLM) judges) are expecte

Beyond Pixels: Benchmarking and Reward-Based Assessing Framework for Visual Spatial Aesthetics

arXiv:2512.05098v2 Announce Type: replace-cross Abstract: In recent years, Image Quality Assessment (IQA) for AI-generated images (AIGI) has advanced rapidly; however, existing methods primarily targe

Beyond Pixels: Exploring DOM Downsampling for LLM-Based Web Agents

arXiv:2508.04412v3 Announce Type: replace Abstract: The advent of large language models (LLMs) has sparked an evolution of autonomous web browsing agents: given a web browsing task and serialised user

Beyond Routing: Decoupling Expert Dispatch and Aggregation in Sparse Mixture-of-Experts

arXiv:2608.08853v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) routers commonly use the same scores both to select experts and to weight their already-computed outputs. We study wheth

Beyond Static Models: An Evolving Framework for Continual Learning in Large Language Models across Training Stages

arXiv:2603.12658v2 Announce Type: replace-cross Abstract: Continual learning (CL) has emerged as a pivotal paradigm to enable large language models (LLMs) to dynamically adapt to evolving knowledge an

Beyond Tables: Doc2DB-Bench for Relationally Faithful Document-to-Database Construction

arXiv:2608.08459v1 Announce Type: cross Abstract: Practical AI systems increasingly need to turn long, heterogeneous documents into queryable relational databases, not isolated spreadsheets. In domain

Beyond the Capability Boundary: Zeroth-Order Optimization for Self-Evolving LLM Agents

arXiv:2608.09292v1 Announce Type: cross Abstract: Self-evolving methods improve the capabilities of LLM agents by sampling trajectories from the underlying LLMs and learning from these trajectories. H

BibTeX Citation Errors in Scientific Publishing Agents: Evaluation and Mitigation

arXiv:2604.03159v2 Announce Type: replace-cross Abstract: Large language models with web search are increasingly used in scientific publishing agents, yet they produce BibTeX entries with pervasive fi

Bidirectional Context Self-Distillation for Reinforcement Learning of Skill-Based LLM Agents

arXiv:2608.09555v1 Announce Type: new Abstract: External natural-language skills provide large language model (LLM) agents with reusable and editable guidance for solving complex tasks. Yet their effe

Biologically Informed Representation Learning for Robust Cross-Center Generalization of MALDI-TOF Mass Spectrometry

arXiv:2608.08182v1 Announce Type: cross Abstract: Machine learning models for MALDI-TOF mass spectrometry have shown considerable promise for clinical microbiology tasks such as microbial identificati

Bridging the Evaluation Gap: Standardized Benchmarks for Multi-Objective Search

arXiv:2603.24084v2 Announce Type: replace Abstract: Empirical evaluation in multi-objective search (MOS) has historically suffered from fragmentation, relying on heterogeneous problem instances with i

Build it, Break it, Repeat: Benchmarking and improving LLM-manipulated disinformation detection in social media posts

arXiv:2608.09510v1 Announce Type: cross Abstract: Detecting machine-generated disinformation on social media is increasingly difficult as large language models (LLMs) make it easier to generate and re

CADEngBench: It Looks Like CAD, but Does It Work? Evaluating Parametric Design, Assembly Reasoning, and Physics Simulation

arXiv:2608.09296v1 Announce Type: new Abstract: A CAD model is not engineering-grade merely because it looks correct. It must satisfy design requirements, respond predictably to parameter changes, sup

Can Graph Learning Learn Circuits?

arXiv:2608.08536v1 Announce Type: new Abstract: Circuit localization is a mechanistic interpretability task whose goal is to identify a sparse subgraph of a transformer's computation graph sufficient

Can LLM Agents Stick to the Script? A Benchmark for Long-Horizon Consistency in Interactive Narratives

arXiv:2608.08160v1 Announce Type: cross Abstract: The rapid advancement of Large Language Models (LLMs) is revolutionizing AI for Games by enabling open-ended and fluid interactive storytelling. Howev

Can Open-Weight Models Compete on Financial Text Comprehension?

arXiv:2608.08634v1 Announce Type: new Abstract: Open-weight language models from Chinese AI labs caught up on benchmarks relative to proprietary frontier models in recent months. Yet their reliability

Can We Optimize the Performance-Carbon Emission Break-Even Point?: The Quest for Greener LLMs

arXiv:2608.08744v1 Announce Type: cross Abstract: The carbon footprint of any deployed Large Language Model (LLM) accumulates during inference, where repeated use of the model substantially exceeds th

CAP: A Scalable Benchmark for Evaluating Cross-Site Browser Agents with Complex Actions and Perception

arXiv:2608.08392v1 Announce Type: new Abstract: Large language models are increasingly deployed as autonomous agents that interact with the web through browsers. While recent progress has been driven

CausalNav: Reliability-Certified Causal World Models for Control under Physical-Parameter Shift

arXiv:2608.07809v1 Announce Type: new Abstract: A world model is only useful for physical AI if it changes what the agent does, and only safe if it declines to do so when it is wrong. We study both ha

CGRL: Causal-Guided Representation Learning for Node-Level Out-of-Distribution Generalization

arXiv:2603.24304v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) deliver strong performance on graph tasks, but their accuracy drops significantly under out-of-distribution (OOD)

ChronoState: Hidden Elapsed-Time Conditioning for Temporal-State Action Selection in Frozen-Backbone Language Models

arXiv:2608.09124v1 Announce Type: new Abstract: Temporal decisions in language-model systems often depend on both symbolic task state and elapsed wall-clock time, such as cache expiration, job complet

CIDER: A Dataset of Contextual Disclosure Boundaries for Privacy Preference Alignment

arXiv:2608.09164v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human privacy preferences requires capturing individuals' disclosure boundaries beyond general privacy norms.

Circuit Fine-Tuning for Compute-Efficient Transformer Adaptation

arXiv:2608.08336v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) has become the de facto standard for adapting Vision Transformers (ViTs) to downstream tasks. While parameter cou

CircuitReason-1k: Benchmarking Long-Horizon Visual-to-Symbolic Reasoning inElectrical Circuits

arXiv:2608.09374v1 Announce Type: new Abstract: Electrical circuit analysis requires more than recognizing components in an image. A solver must ground symbols and labels, recover latent topology, sel

CliniCARE-Bench: Clinical Calibrated Audit of Medical Reasoning in EHR

arXiv:2608.07796v1 Announce Type: new Abstract: Large language models perform strongly on medical knowledge benchmarks, but reliable clinical deployment requires agents to conduct defensible investiga

Closing the loop in learning with missing data

arXiv:2608.09030v1 Announce Type: cross Abstract: What should a machine learning model learn when data is missing during training? We look at the learning process from a dynamical systems perspective,

CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models

arXiv:2608.07621v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently achieved impressive performance for end-to-end autonomous driving, yet existing approaches are primari

CodecArena: Codec Quality Assessment via Visual Reinforcement Learning

arXiv:2608.09139v1 Announce Type: new Abstract: Video coding is advancing into the low and ultra-low bitrate regime, driven by end-to-end codecs that replace the hand-crafted pipeline with jointly opt

ComboShoppingBench: Evaluating LLM Agents for Budget-Constrained Basket Shopping with Coupons

arXiv:2608.09282v1 Announce Type: new Abstract: Real-world shopping often requires constructing a basket of complementary items rather than retrieving a single product. Such combo-shopping tasks arise

COMEX: A Composition-Grounded Benchmark and Learning Framework for Explainable Aesthetic Image Cropping

arXiv:2608.07570v1 Announce Type: cross Abstract: Explainable aesthetic image cropping requires not only localizing a visually pleasing crop but also explaining why it is preferred. Existing crop-and-

Compiling and Benchmarking Task-State Horizons for Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2608.08036v1 Announce Type: new Abstract: Frontier agentic models are increasingly deployed as high-level planners for long-horizon embodied tasks. Existing robotic benchmarks have advanced long

ComplexityWorld: Benchmarking Vision-Language Models on Verifiable Visual Decision Making

arXiv:2608.07584v1 Announce Type: new Abstract: Vision-language models (VLMs) have made rapid progress in visual perception and increasingly support real-world tasks that depend on images. Many such t

Contamination Means Overestimation? A Fine-Grained Empirical Study in Code Intelligence

arXiv:2506.02791v4 Announce Type: replace-cross Abstract: In recent years, code intelligence has gained increasing importance in the field of automated software engineering. Meanwhile, the widespread

Control-Diverse Reinforcement Fine-Tuning: Decoupling the Shared Control Bottleneck of RL Post-Training

arXiv:2608.08224v1 Announce Type: new Abstract: Reinforcement learning post-training unlocks complex reasoning in LLMs. Yet benchmark scores reveal only whether a model improved, not what changed insi

Conversation as Measurement in Clinical Encounters: Observable Phase Structure, Partially Observable Patient State

arXiv:2608.08868v1 Announce Type: new Abstract: Many modern AI systems analyze conversational traces to infer aspects of human interaction and state, implicitly assuming that such information is recov