Search: “model-releases”

Stress-Testing EEG Foundation Models for Clinical Decoding: Dataset Identity and Targeted Negative Controls

arXiv:2607.24519v1 Announce Type: cross Abstract: Pretrained EEG foundation models are increasingly proposed for clinical decoding, but their transfer across populations and robustness to negative con

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Model Releases

Subject-Level Heterogeneity in EEG Motor Imagery Decoding: A Large-Scale Benchmark and Portfolio-Based Reduction of the Search Space

DGX agent

arXiv:2607.22778v1 Announce Type: cross Abstract: Robust EEG motor imagery decoding remains limited by strong inter-individual variability, making it difficult to identify pipelines that generalize ac

model-releasesarxiv-cs-lg

28 Jul 2026

Success Is Not Self-Explanatory: Auditing Success Provenance in Agent Evaluation

arXiv:2607.24054v1 Announce Type: new Abstract: A correct answer can conceal why an agent succeeded. Once agents change their information state during evaluation, correctness no longer distinguishes i

SymStep: Symbolic Step Verification for Logical Reasoning

arXiv:2607.23055v1 Announce Type: new Abstract: Chain-of-thought (CoT) prompting can fail severely on constraint-dense logical reasoning tasks, where unverified errors accumulate silently across steps

Tag Questions and the Generational Reversal of Sycophancy Across 45 Language Models

arXiv:2607.23976v1 Announce Type: cross Abstract: Appending a two-word confirmation tag to a decision question -- 'Is X the better choice?' versus 'X is the better choice, right?' -- changes whether a

TEmBed-T: A Multi-Dimensional Benchmark for Table-Level Embeddings

arXiv:2607.24130v1 Announce Type: cross Abstract: Tabular data is the dominant structured-data modality, and learning table representations has become a core research direction. Table-level embeddings

TextRich: A Multi-Domain Benchmark for Detecting AI-Generated Text-Rich Images from GPT-Image-2

arXiv:2606.19259v2 Announce Type: replace-cross Abstract: Text-rich images often contain privacy-sensitive, transactional, or decision-relevant information. As recent multimodal image generation model

The Cost of Knowing: A Resource-Aware Protocol for Benchmarking Hallucination Beyond Static Leaderboards

arXiv:2607.24063v1 Announce Type: new Abstract: On standard factuality tasks, frontier models now cluster near the top of the scale. The question is therefore shifting from how factual a system is tow

The Few-shot Dilemma: Over-prompting Large Language Models

arXiv:2509.13196v2 Announce Type: replace Abstract: Over-prompting, a phenomenon where excessive examples in prompts lead to diminished performance in Large Language Models (LLMs), challenges the conv

The Gate Always Closes: On Injecting Auxiliary Signals into Frozen Vision-Language Models

arXiv:2607.23335v1 Announce Type: new Abstract: Auxiliary signal pathways in VLMs are routinely fitted with learnable gates so the optimiser can decide how much of the signal to admit. We find that th

The Half-Lives of Generative-AI Evidence: A 40-Record Audit, a Claim-Currency Framework, and a Reflexive Case of Frontier-Model-Assisted Research

arXiv:2607.24032v1 Announce Type: new Abstract: Generative-AI evaluations can become historical before publication, yet calendar age does not affect every conclusion equally. This paper has two linked

The Label Complexity of Class-Conditional Coverage under Distribution Shift

arXiv:2607.18088v2 Announce Type: replace-cross Abstract: Conformal prediction certifies that a classifier's prediction sets cover the truth, and that certificate is marginal. Many recognition benchma

The Scaffold Effect in Coding Agents: Harness Choice as a Hidden Variable in Coding-Agent Evaluation

arXiv:2607.22585v1 Announce Type: new Abstract: Public leaderboards for coding agents typically rank systems by model name and pass rate, while the surrounding harness (the scaffold that issues tools,

The Tokenizer Tax: Quantifying and Explaining the Cross-Lingual Cost of Subword Tokenization for Indian Languages

arXiv:2607.24276v1 Announce Type: cross Abstract: Large language models (LLMs) process text through subword tokenizers rather than directly reading characters or words. Because these tokenizers are tr

Through the Bottleneck: How Multi-head Latent Attention Separates Content from Position in Language Models

arXiv:2607.23054v1 Announce Type: cross Abstract: Multi-head Latent Attention (MLA), introduced in DeepSeek-V2, compresses key-value pairs through a shared low-rank bottleneck (cKV), achieving 81% KV-

TimePLE: Rethinking Temporal Representation for Video Temporal Grounding

arXiv:2607.23951v1 Announce Type: new Abstract: Video temporal grounding (VTG) aims to localize the continuous video interval described by a natural-language query. However, current VLM-based methods

TLA^{+}-Bench: An Execution-Grounded Benchmark and Dataset for Natural-Language to TLA+ Specification Generation

arXiv:2607.23425v1 Announce Type: cross Abstract: Large language models increasingly write TLA^{+} formal specifications from natural-language descriptions, but progress is hard to measure: existing r

TLRNet: Estimating Individual Treatment Effect based on Local Information and Single Learner Structure

arXiv:2607.22762v1 Announce Type: cross Abstract: Causal inference has become a central issue across various fields, including computer science, statistics, economics, education, healthcare, and medic

Tokengeist: Multi-Turn Attribution Tracing in Agentic Conversations

arXiv:2607.22610v1 Announce Type: new Abstract: When a language model produces a response in a multi-turn conversation, which tokens from prior turns shaped that answer, and how did those dependencies

TokenMem: Faithful Knowledge Injection for Frozen LLMs

arXiv:2607.22625v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enhances large language models (LLMs) with external knowledge, but suffers from knowledge conflicts: when retrieved

Toward Automated Detection of Documentation Inconsistencies in Electronic Health Records

arXiv:2607.22954v1 Announce Type: new Abstract: Objective: To characterize the kinds of internal documentation inconsistencies a general-domain large language model (LLM) can surface from real-world d

Towards simultaneous decoding of kinetic and kinematic movement parameters during grasp and lift task by noninvasive brain imaging

arXiv:2607.24081v1 Announce Type: cross Abstract: Brain-machine interfaces (BMIs) can assist individuals with limited mobility, such as stroke survivors or amputees. One of the key challenges in devel

Transfer Learning Architectures for Scalable Multi-Fidelity Bayesian Optimization

arXiv:2607.23404v1 Announce Type: new Abstract: Self-driving laboratories increasingly rely on multi-fidelity Bayesian optimization (MFBO) to balance cheap, approximate evaluations against scarce, exp

TRE: Training-Free Hallucination Detection for Diffusion Language Models

arXiv:2607.22661v1 Announce Type: new Abstract: Diffusion large language models (D-LLMs) have recently gained increasing attention, yet their reliability is significantly hindered by the hallucination

TRIDENT: Benchmarking LLM Safety in Finance, Medicine, and Law

arXiv:2507.21134v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in high-risk domains such as law, finance, and medicine, systematically evaluating their d

TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation

arXiv:2607.23838v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) lets a large language model answer questions using documents retrieved from an external knowledge base at query t

TriSP: Tri-Signal Structured Pruning for Large Language Models

arXiv:2607.22587v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance across diverse tasks but their deployment is constrained by the memory and compute cost of their

Trustworthy Medical Segmentation: Uncertainty-Aware U-Net Evaluation Under Clinical Image Degradation

arXiv:2607.22727v1 Announce Type: new Abstract: Medical image segmentation models often report high benchmark accuracy under ideal imaging conditions, yet their failures under clinical degradation can

Try Once, Then Optimal: De-Redundified Procedure Memory for Cross-Episode Exploration Amortization

model-releasesarxiv-cs-ro

arXiv:2607.23702v1 Announce Type: new Abstract: Manipulating objects with hidden internal state, such as a latched microwave, forces a robot to probe before it can act. Yet a robot that has solved an

Two Regimes of Chain-of-Thought Unfaithfulness: Behavioral Detection Fails Where Models Are Wrong

arXiv:2607.23458v1 Announce Type: new Abstract: Chain-of-thought (CoT) explanations support oversight only if they are faithful: the stated reasoning must actually produce the answer. Auditing black-b

Two-Timescale Hierarchical Reinforcement Learning for Resilient Operations

arXiv:2607.23434v1 Announce Type: cross Abstract: Unexpected shocks recur in global operations, requiring decision rules that adapt as market and operating conditions change. Many operational systems

UAV-ON: A Benchmark for Open-World Object Goal Navigation with Aerial Agents

arXiv:2508.00288v5 Announce Type: replace-cross Abstract: Aerial navigation is a fundamental yet underexplored capability in embodied intelligence, enabling agents to operate in large-scale, unstructu

Understanding Machine Unlearning Through the Lens of Mode Connectivity

arXiv:2607.23970v1 Announce Type: cross Abstract: Machine Unlearning aims to remove undesired information from trained models without full retraining from scratch. Despite recent progress, the loss la

Understanding Tone-Dependent Inference Cost in Large Language Models

arXiv:2607.23915v1 Announce Type: cross Abstract: We examine how prompt tone affects both accuracy of the LLM answers and inference cost as reflected in output-token consumption. Experiments were perf

Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training

arXiv:2512.24125v3 Announce Type: replace-cross Abstract: General-purpose robotic systems operating in open-world environments must achieve both broad generalization and high-precision action executio

UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective

arXiv:2607.24507v1 Announce Type: cross Abstract: Existing methods mainly adapt pretrained autoregressive (AR) language models to masked diffusion, whereas we directly adapt them to uniform-noise diff

Unsupervised Graph Representation Learning with Complementary View Alignment

arXiv:2607.24338v1 Announce Type: new Abstract: Unsupervised graph representation learning aims to derive meaningful node embeddings by capturing both structural and attribute information without rely

UP-Fuse: Uncertainty-guided LiDAR-Camera Fusion for 3D Panoptic Segmentation

arXiv:2602.19349v2 Announce Type: replace-cross Abstract: LiDAR-camera fusion enhances 3D panoptic segmentation by leveraging camera images to complement sparse LiDAR scans, but it also introduces a c

Using Reinforcement Learning to Optimize the Global and Local Crossing Number

arXiv:2509.06108v3 Announce Type: replace-cross Abstract: Graph drawing concerns the algorithmic visualization of graphs. A good drawing of a graph is easy to read and facilitates solving tasks on the

Variational Quantum Conditional Boltzmann Machines for Time-Series Forecasting: Architectures, Symmetric Hyperparameter Evaluation, and a Nonlinear Benchmark

arXiv:2607.24065v1 Announce Type: cross Abstract: In this study, we developed and evaluated four conditional energy-based forecasting architectures: a classical Gaussian-Bernoulli CRBM, a hybrid quant

Verbalized Particle Posterior: Bayesian Inference over Natural Language Hypotheses

arXiv:2607.22961v1 Announce Type: cross Abstract: Verbalized Machine Learning (VML) parameterizes a model as a natural-language prompt that an LLM evaluates as f(x; theta). The framework is interpreta

Visible-Light Imaging Diagnosis of Neutral Particle Emission Tomography in the Tokamak Divertor: An Efficient Transformer-based Surrogate Model

arXiv:2607.22704v1 Announce Type: cross Abstract: Nuclear fusion has made significant progress in recent years and is expected to become one of the most important pathways to addressing global energy

VL-LN Bench: Towards Long-horizon Goal-oriented Navigation with Active Dialogs

model-releasesarxiv-cs-ro

arXiv:2512.22342v5 Announce Type: replace Abstract: In most existing embodied navigation tasks, instructions are well-defined and unambiguous, such as instruction following and object searching. Under

VlogReward: Learning Multi-Dimensional Evaluation for Vlog Editing

arXiv:2607.22632v1 Announce Type: new Abstract: The rapid rise of vlogs as a personalized storytelling medium has created a demand for automated systems to evaluate and refine vlog editing plans. Howe

Weighted Low-Rank Matrix Approximation: Acceleration and Applications

arXiv:2109.11057v2 Announce Type: replace-cross Abstract: Weighted low-rank matrix approximation (WLRMA) generalizes classical low-rank approximation and matrix completion by allowing arbitrary elemen

When Less Is More: A Controlled Benchmark of Lightweight CNNs for Satellite Land-Cover Segmentation on DeepGlobe

arXiv:2607.23024v1 Announce Type: new Abstract: High-resolution satellite imagery is the backbone of good land-cover classification, and without that, environmental monitoring, urban planning, and sus

When LLM Defenses Backfire: Characterizing Safety, Performance, and Cost Trade-offs

arXiv:2607.24392v1 Announce Type: cross Abstract: Jailbreak defenses are essential for protecting large language models (LLMs), but they can also introduce secondary costs that weaken model utility. W

When Low CER is Not Enough: An Analysis of Hallucinations in Vision-Language OCR Systems on Historical Uruguayan Documents

arXiv:2607.24077v1 Announce Type: new Abstract: Optical Character Recognition (OCR) is a key component in the digitization of historical archives. Recently, Vision-Language Models (VLMs) have emerged