Search: “model-releases”

Text-to-CAD Evaluation with CADTests

arXiv:2605.07807v1 Announce Type: cross Abstract: Text-to-CAD has recently emerged as an important task with the potential to substantially accelerate design workflows. Despite its significance, there

The Convergence Gap: Instruction-Tuned Language Models Stabilize Later in the Forward Pass

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DGX agent

arXiv:2605.07282v1 Announce Type: new Abstract: Final outputs hide when a checkpoint commits to its next-token prediction. We introduce the convergence gap, a model-diffing diagnostic that decodes eac

model-releasesarxiv-cs-lg

11 May 2026

The Coupling Tax: How Shared Token Budgets Undermine Visible Chain-of-Thought Under Fixed Output Limits

arXiv:2605.07686v1 Announce Type: new Abstract: Chain-of-thought reasoning is often treated as a monotone way to improve language-model accuracy by letting a model think longer. We identify a counterv

The Memory Curse: How Expanded Recall Erodes Cooperative Intent in LLM Agents

arXiv:2605.08060v1 Announce Type: cross Abstract: Context window expansion is often treated as a straightforward capability upgrade for LLMs, but we find it systematically fails in multi-agent social

The Position Curse: LLMs Struggle to Locate the Last Few Items in a List

arXiv:2605.07127v1 Announce Type: cross Abstract: Modern large language models (LLMs) can find a needle in a haystack (locating a single relevant fact buried among hundreds of thousands of irrelevant

The Single-File Test: A Longitudinal Public-Interface Evaluation of First-Output LLM Web Generation with Social Reach Tracking

arXiv:2605.06707v1 Announce Type: cross Abstract: This paper presents an eight-week observational comparison of 68 single-file HTML generations collected across 17 public experiments in the 'HTML AI B

The Text Uncanny Valley: Non-Monotonic Performance Degradation in LLM Information Retrieval

arXiv:2605.07186v1 Announce Type: cross Abstract: Existing Large Language Model (LLM) benchmarks primarily focus on syntactically correct inputs, leaving a significant gap in evaluation on imperfect t

The Translation Tax Is Not a Scalar: A Counterfactual Audit of English-Source Cue Inheritance in Chinese Multilingual Benchmarks

arXiv:2605.07093v1 Announce Type: cross Abstract: The Translation Tax is often treated as a scalar: translated benchmarks are assumed to inflate scores by preserving English-source cues. We audit this

Theory of Optimal Learning Rate Schedules and Scaling Laws for a Random Feature Model

arXiv:2602.04774v2 Announce Type: replace-cross Abstract: Setting the learning rate (LR) for a deep learning model is a critical part of successful training. Choosing LRs is often done empirically wit

THINKSAFE: Self-Generated Safety Alignment for Reasoning Models

arXiv:2601.23143v2 Announce Type: replace Abstract: Large reasoning models (LRMs) achieve remarkable performance by leveraging reinforcement learning (RL) on reasoning tasks to generate long chain-of-

ThinKV: Thought-Adaptive KV Cache Compression for Efficient Reasoning Models

arXiv:2510.01290v2 Announce Type: replace Abstract: The long-output context generation of large reasoning models enables extended chain of thought (CoT) but also drives rapid growth of the key-value (

Toeplitz MLP Mixers are Low Complexity, Information-Rich Sequence Models

arXiv:2605.06683v1 Announce Type: cross Abstract: Transformer-based large language models are in some respects limited by the quadratic time and space computational complexity of attention. We introdu

Tool Calling is Linearly Readable and Steerable in Language Models

arXiv:2605.07990v1 Announce Type: cross Abstract: When a tool-calling agent picks the wrong tool, the failure is invisible until execution: the email gets sent, the meeting gets missed. Probing 12 ins

Tools as Continuous Flow for Evolving Agentic Reasoning

arXiv:2605.07339v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in orchestrating tools for reasoning tasks. However, existing methods rely on a s

Topic Is Not Agenda: A Citation-Community Audit of Text Embeddings

arXiv:2605.07158v1 Announce Type: cross Abstract: Vector search and retrieval-augmented generation (RAG) rest on the assumption that cosine similarity between text embeddings reflects conceptual relat

Towards Closing the Autoregressive Gap in Language Modeling via Entropy-Gated Continuous Bitstream Diffusion

arXiv:2605.07013v1 Announce Type: new Abstract: Diffusion language models (DLMs) promise parallel, order-agnostic generation, but on standard benchmarks they have historically lagged behind autoregres

TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos

model-releasesarxiv-cs-cv

arXiv:2605.07593v1 Announce Type: new Abstract: Real-world audio-visual understanding requires chaining evidence that is sparse, temporally dispersed, and split across the visual and auditory streams,

Tracing Uncertainty in Language Model 'Reasoning'

arXiv:2605.07776v1 Announce Type: cross Abstract: Language model (LM) 'reasoning', commonly described as Chain-of-Thought or test-time scaling, often improves benchmark performance, but the dynamics u

Traffic Scenario Orchestration from Language via Constraint Satisfaction

model-releasesarxiv-cs-ro

arXiv:2605.06966v1 Announce Type: new Abstract: Autonomous vehicles (AVs) require extensive testing in simulation, but test case generation for driving scenarios is laborious. The desired scenarios ar

Training-Induced Escape from Token Clustering in a Mean-Field Formulation of Transformers

arXiv:2605.07772v1 Announce Type: new Abstract: Transformers perform inference by iteratively transforming token representations across layers. This layerwise computation has been studied empirically,

Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation

arXiv:2605.07924v1 Announce Type: cross Abstract: Discrete flow matching generates text by iteratively transforming noise tokens into coherent language, but may require hundreds of forward passes. Dis

TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models

arXiv:2601.18744v2 Announce Type: replace Abstract: Time series are ubiquitous in real-world scenarios and crucial for applications ranging from energy management to traffic control. Consequently, the

UNCOM: Zero-shot Context-Aware Command Understanding for Tabletop Scenarios

arXiv:2410.06355v3 Announce Type: replace-cross Abstract: This paper presents UNCOM, a novel hybrid framework for interpreting natural human commands in tabletop scenarios. The system integrates multi

Understanding Robustness of Model Editing in Code LLMs

arXiv:2511.03182v2 Announce Type: replace-cross Abstract: Large language models (LLMs) for code are increasingly used in software development, but they remain static after pretraining while APIs and s

Uneven Evolution of Cognition Across Generations of Generative AI Models

arXiv:2605.06815v1 Announce Type: new Abstract: The pursuit of artificial general intelligence necessitates robust methods for evaluating the cognitive capabilities of models beyond narrow task perfor

Unsolvability Ceiling in Multi-LLM Routing: An Empirical Study of Evaluation Artifacts

arXiv:2605.07395v1 Announce Type: cross Abstract: Efficient routing across multiple LLMs enables cost-quality tradeoffs by directing queries to the cheapest capable model. Prior work attributes routin

Utility-Preserving De-Identification for Math Tutoring: Investigating Numeric Ambiguity in the MathEd-PII Benchmark Dataset

arXiv:2602.16571v2 Announce Type: replace Abstract: Large-scale sharing of dialogue data is key to advancing the science of teaching and learning, yet rigorous de-identification remains a major barrie

Video Understanding Reward Modeling: A Robust Benchmark and Performant Reward Models

arXiv:2605.07872v1 Announce Type: cross Abstract: Multimodal reward models have advanced substantially in text and image domains, yet progress in video understanding reward modeling remains severely l

Visual Text Compression as Measure Transport

arXiv:2605.06708v1 Announce Type: cross Abstract: Visual text compression (VTC) promises efficient long-context processing by rendering text into an image and re-encoding it with a vision-language mod

VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts

model-releasesarxiv-cs-ro

arXiv:2605.06175v2 Announce Type: replace Abstract: Vision-language-action (VLA) models inherit rich visual-semantic priors from pre-trained vision-language backbones, but adapting them to robotic con

When Are Experts Misrouted? Counterfactual Routing Analysis in Mixture-of-Experts Language Models

arXiv:2605.07260v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models route each token to a small subset of experts, but whether the routes selected by a trained top-k router are

When Does Critique Improve AI-Assisted Theoretical Physics? SCALAR: Structured Critic--Actor Loop for Agentic Reasoning

arXiv:2605.06772v1 Announce Type: new Abstract: As large language models (LLMs) show increasing promise on research-level physics reasoning tasks and agentic AI becomes more common, a practical questi

When Routine Chats Turn Toxic: Unintended Long-Term State Poisoning in Personalized Agents

arXiv:2605.06731v1 Announce Type: cross Abstract: Personalized LLM agents maintain persistent cross-session state to support long-horizon collaboration. Yet, this persistence introduces a subtle but c

Where to Spend Rollouts: Hit-Utility Optimal Rollout Allocation for Group-Based RLVR

arXiv:2605.07114v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a central paradigm for improving the reasoning capabilities of large language model

Where's the Plan? Locating Latent Planning in Language Models with Lightweight Mechanistic Interventions

arXiv:2605.07984v1 Announce Type: cross Abstract: We study planning site formation in language models -- where internal representations of structurally-constrained future tokens form during the forwar

Why Self-Inconsistency Arises in GNN Explanations and How to Exploit It

arXiv:2605.07527v1 Announce Type: cross Abstract: Recent work has observed that explanations produced by Self-Interpretable Graph Neural Networks (SI-GNNs) can be self-inconsistent: when the model is

WiCER: Wiki-memory Compile, Evaluate, Refine Iterative Knowledge Compilation for LLM Wiki Systems

arXiv:2605.07068v1 Announce Type: cross Abstract: The LLM Wiki pattern, to compile and provide domain knowledge into a persistent artifact and serve it to LLMs via KV cache inference, promises context

Your Language Model is Its Own Critic: Reinforcement Learning with Value Estimation from Actor's Internal States

arXiv:2605.07579v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) for Large Reasoning Models hinges on baseline estimation for variance reduction, but existing ap

A Biased Nonnegative Block Term Tensor Decomposition Model for Dynamic QoS Prediction

arXiv:2605.04813v1 Announce Type: new Abstract: With the rapid development of cloud computing and Web services, Quality of Service (QoS) has become a key criterion for service selection and recommenda

A Comparative Study of PyCaret AutoML and CNN-BiLSTM for Binary Hate Speech Detection in Indonesian Twitter

arXiv:2605.04885v1 Announce Type: new Abstract: This paper compares a PyCaret AutoML branch and a CNN-BiLSTM branch for binary hate speech detection on Indonesian Twitter using the HS label from the c

A Regulatory Governance Framework for AI-Driven Financial Fraud Detection in U.S. Banking: Integrating OCC, SR 11-7, CFPB, and FinCEN Compliance Requirements for Model Development, Validation, and Monitoring Lifecycles

arXiv:2605.04076v1 Announce Type: new Abstract: U.S. financial institutions deploying AI-based fraud detection face a fragmented compliance landscape spanning four regulatory frameworks -- OCC Bulleti

A Scalable Multi-Task Model for Virtual Sensors

arXiv:2601.20634v2 Announce Type: replace Abstract: Virtual sensors replace expensive physical sensors in critical applications through machine learning by predicting target signals from available mea

A Self-Attentive Meta-Optimizer with Group-Adaptive Learning Rates and Weight Decay

arXiv:2605.04055v1 Announce Type: new Abstract: Adaptive optimizers like AdamW apply uniform hyperparameters across all parameter groups, ignoring heterogeneous optimization dynamics across layers and

A unified Benchmark for Multi-Frame Image Restoration under Severe Refractive Warping

model-releasesarxiv-cs-cv

arXiv:2605.05079v1 Announce Type: new Abstract: Video sequence capturing through refractive dynamic media, such as a turbulent air or water surface, often suffer from severe geometric distortions and

A Universal Large Language Model -- Drone Command and Control Interface

model-releasesarxiv-cs-ro

arXiv:2601.15486v2 Announce Type: replace Abstract: The use of artificial intelligence (AI) for drone control can have a transformative impact on drone capabilities, especially when real world informa

Adapting Large Language Models to a Low-Resource Agglutinative Language: A Comparative Study of LoRA and QLoRA for Bashkir

arXiv:2605.04948v1 Announce Type: new Abstract: This paper presents a comparative study of parameter-efficient fine-tuning (PEFT) methods, including LoRA and QLoRA, applied to the task of adapting lar

Adaptive Ensemble Aggregation for Actor-Critics

arXiv:2507.23501v2 Announce Type: replace Abstract: Ensembles are ubiquitous in off-policy actor-critic learning, yet their efficacy depends critically on how they are aggregated. Current methods typi

Aes3D: Aesthetic Assessment in 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2605.05155v1 Announce Type: new Abstract: As 3D Gaussian Splatting (3DGS) gains attention in immersive media and digital content creation, assessing the aesthetics of 3D scenes becomes important