Search: “model-releases”

Conservation laws determine what physical learning remembers

arXiv:2608.00097v1 Announce Type: cross Abstract: Physical learning rules such as equilibrium propagation (EP), coupled learning (CL), and adjoint coupled learning (AL) train resistive networks throug

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Control Under Compression: Reliability Frontiers for Tool-Using Agents

DGX agent

arXiv:2608.01056v1 Announce Type: cross Abstract: Tool-using language-model agents are governed not only by task prompts but also by persistent system-side instructions that specify tools, arguments,

model-releasesarxiv-cs-cl

4 Aug 2026

Cooperative Coevolution for Resource-Constrained Agentic LLM Post-Training

arXiv:2608.02391v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents produce long, multi-turn trajectories, making gradient-based post-training memory-intensive. Evolution st

CORTIVA: Candidate-Score Fusion of Complementary Visual Teachers for EEG- and MEG-to-Image Retrieval

arXiv:2608.01355v1 Announce Type: new Abstract: Decoding visual experience from non-invasive brain activity is central to neuroscience and brain-computer interfaces. Functional magnetic resonance imag

Cost-Effective Automated Judging of Natural-Language Mathematical Proofs

arXiv:2608.00004v1 Announce Type: new Abstract: Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whe

CoSynFlow: Conformal Symplectic Neural Flows for Cross-System Prediction of Dissipative Hamiltonian Dynamics

arXiv:2608.00571v1 Announce Type: new Abstract: Learning solution operators for differential equations is a central problem in scientific machine learning. However, many neural operator methods optimi

CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models

arXiv:2608.01644v1 Announce Type: new Abstract: In video understanding, vision-language models (VLMs) must ingest massive numbers of visual tokens, causing the computational and memory cost of the pre

CRIP: Channel Level Representation Injection for Personalized One-Shot Federated Learning

arXiv:2608.02222v1 Announce Type: new Abstract: One-shot federated learning (OSFL) has emerged as a promising collaborative model learning framework with only a single round of communication, offering

CrossLex: A Source-Grounded Benchmark for Cross-Jurisdictional Legal Reasoning in Large Language Models

arXiv:2608.01292v1 Announce Type: new Abstract: Legal reasoning is inherently jurisdiction-dependent: the same facts can call for different legal rules and yield different conclusions across legal sys

CrossProjection: Geometric Grounding Beyond Viewpoint Change in Architectural Drawings

arXiv:2608.00473v1 Announce Type: cross Abstract: Architectural drawings violate the usual assumption behind multi-view reasoning: plans and sections are cuts, while elevations are facade projections,

Crushing the Evidence: A Dual-Penalty Evasion Framework for Fooling White-Box Explainable AI Auditors

arXiv:2608.00566v1 Announce Type: new Abstract: Post-hoc model explainers such as LIME, SHAP, and Integrated Gradients are widely deployed to audit models in high-stakes sensitive domains, including f

CultureVidBench: Benchmarking Cultural Understanding in Text-to-Video Generation

arXiv:2608.01942v1 Announce Type: cross Abstract: Text-to-video (T2V) generation models have advanced rapidly, yet their ability to represent diverse cultural contexts remains underexplored. Existing

CurveShift: Is Agent Progress Scalar? Separating Level from Shape

arXiv:2608.00355v1 Announce Type: new Abstract: Progress in large language models is often summarized using a single scalar measure, such as a time horizon, a latent ability estimate, or an aggregate

Data-Driven Pinball-Loss Selection for Vertically Distributed Elastic-Net SVMs

arXiv:2608.00949v1 Announce Type: new Abstract: The pinball-loss support vector machine is robust, but its asymmetry parameter is usually fixed in advance. We propose a data-driven elastic-net support

DE-NER : Zero-shot Named Entity Recognition via Dialogue Elicitation of Large Language Models

arXiv:2608.00538v1 Announce Type: new Abstract: Recent advancements of zero-shot Named Entity Recognition (NER) establish strong baselines by formulating sequence labeling into question answering wher

DeBERTa-Sentinel: Toward Transparent and Trustworthy Detection of AI-Generated Text

arXiv:2608.01046v1 Announce Type: new Abstract: The rapid spread of large language models (LLMs) across the web raises concerns about misinformation, academic integrity, automated content manipulation

DeCLIP: Decoupled Prompting for Multi-Label Class-Incremental Learning with CLIP

arXiv:2509.23335v3 Announce Type: replace Abstract: Multi-label class-incremental learning (MLCIL) continuously expands the label space while recognizing multiple co-occurring categories, making catas

Decoupling semantics from vision: A framework for faithful visual-text compression evaluation

arXiv:2608.01848v1 Announce Type: new Abstract: Recent visual-text compression (VTC) methods, typified by DeepSeek-OCR, report impressive high token compression ratios for long-context modeling tasks

Deep Learning for Cyber Threat Detection and Mitigation in Healthcare-IoT

arXiv:2608.00118v1 Announce Type: cross Abstract: Cybersecurity is a fundamental requirement for protecting wearable devices used in healthcare Internet of Things (H-IoT) systems. Security failures in

Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge

arXiv:2506.02976v4 Announce Type: replace Abstract: The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) thro

DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Surveys

arXiv:2601.15307v2 Announce Type: replace-cross Abstract: The rapid development of automated survey generation technology has made it increasingly important to establish a comprehensive benchmark to e

Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning

arXiv:2410.06814v2 Announce Type: replace Abstract: Over-parameterized models are typically vulnerable to membership inference attacks, which aim to determine whether a specific sample is included in

DeltaFlow: Noise-Adaptive Bidirectional Gated Delta Networks for Embedded Language Flows

arXiv:2608.01240v1 Announce Type: new Abstract: Embedded Language Flows (ELF) rely primarily on full non-causal attention for iterative denoising, repeatedly incurring quadratic sequence-mixing cost a

Deployment-Ready UWB Localization for Industrial Ground Robots with Automatic Anchor Calibration and Terrain-Aware Fusion

model-releasesarxiv-cs-ro

arXiv:2607.15807v2 Announce Type: replace Abstract: Ultra-Wideband (UWB) ranging has become a viable option for industrial Autonomous Mobile Robot (AMR) localization due to improved accuracy and low c

Detail Continuation over a Trustworthy Coarse Scale for Autoregressive Super-Resolution

arXiv:2608.01823v1 Announce Type: new Abstract: Hallucination remains a persistent challenge in generative super-resolution (GSR), where reconstructed results may contain visually plausible yet weakly

DiffusionGemma Technical Report

arXiv:2608.00146v1 Announce Type: new Abstract: We introduce DiffusionGemma, an experimental open-weight language model that uses discrete diffusion to generate text at exceptionally high speed. Rathe

Disentangling Visuo-Tactile Foresight: Oracle-Guided Interface Discovery for World Action Models

model-releasesarxiv-cs-ro

arXiv:2608.00547v1 Announce Type: new Abstract: Contact-rich manipulation remains challenging because successful control depends on physical interaction cues that are often weakly observable from visi

Divergent large language model predictions from convergent representations in ambiguous word pairs

arXiv:2608.01816v1 Announce Type: new Abstract: In this work we investigate how decoder-only transformers resolve lexical ambiguity through layer-by-layer analysis of three models spanning three param

DLLM-TTS: Block Discrete Diffusion Language Model for Text-to-Speech Synthesis

arXiv:2608.00011v1 Announce Type: new Abstract: Current text-to-speech systems face a trade-off: autoregres- sive codec language models produce highly intelligible speech but require large-scale model

Do Maps Still Matter for Machines: Revisiting the Role of Choropleth Maps in Foundation Model Spatial Understanding

arXiv:2607.17999v2 Announce Type: replace-cross Abstract: Spatial understanding is crucial for foundation models (FMs), and maps have long helped humans organize and reason about geographic informatio

Do Static Embeddings Add Value to Hybrid Dutch Retrieval?

arXiv:2608.02112v1 Announce Type: new Abstract: Embedding benchmarks measure standalone model quality, but they do not establish whether a low-cost retriever contributes complementary ranking informat

Does Explainability Transfer? A Controlled Benchmark of Attribution Methods on Vision Transformers and CNNs

arXiv:2608.02396v1 Announce Type: new Abstract: Most evidence on the effectiveness of explainable artificial intelligence (XAI) attribution methods has been established on convolutional neural network

Domain-Specific Evaluation of Text-to-Speech Systems: A Multi-Metric Benchmarking Study

arXiv:2608.02235v1 Announce Type: new Abstract: Recent advances in neural text-to-speech (TTS) systems have substantially improved speech naturalness and intelligibility across many languages. However

Don't Judge a Book by its Cover: Testing LLMs' Robustness Under Logical Obfuscation

arXiv:2602.01132v2 Announce Type: replace Abstract: Tasks such as solving arithmetic equations, evaluating truth tables, and completing syllogisms are handled well by large language models (LLMs) in t

DrawAI: Agentic Benchmark and Workflow for Making Raster Images Editable

arXiv:2608.00548v1 Announce Type: new Abstract: Recent image-generation models and multimodal agents can produce high-quality visuals for increasingly complex visual communication tasks. Yet their ras

DS@GT ARC at MEDIQA-CORE-Task-1 2026: Trimodal Model Fusion with Task-Specific Gates for Brain Tumor Subtype Classification

arXiv:2608.00086v1 Announce Type: new Abstract: Brain tumor diagnosis is a time-sensitive process in which patients may wait weeks for a finalized pathology report. This problem motivates automated sy

DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration

arXiv:2608.01452v1 Announce Type: cross Abstract: Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that a

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers

arXiv:2607.17244v2 Announce Type: replace Abstract: Longitudinal T cell receptor repertoires contain signals of clonal expansion, contraction, disappearance, and reappearance after immune perturbation

E2Pano: Learning Event-to-Panorama Image Reconstruction

arXiv:2608.00694v1 Announce Type: new Abstract: Event cameras offer microsecond-level temporal resolution and high dynamic range, potentially facilitating motion-blur-free panoramic imaging from fast

EchoCache: Energy-Guided Cross-Modal Caching for Efficient Audio-Driven Video Generation

arXiv:2608.02474v1 Announce Type: new Abstract: Audio-driven video generation (A2V) has achieved promising progress in synthesizing temporally coherent and audio-visually aligned videos, yet its infer

EEG-FM-Compass: Progress, Benchmarking, and Future Directions for EEG Foundation Models

arXiv:2601.17883v3 Announce Type: replace-cross Abstract: Electroencephalography (EEG) foundation models (FMs) have recently emerged as a promising paradigm for brain-computer interfaces, aiming to le

Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs

arXiv:2511.00382v2 Announce Type: replace-cross Abstract: Organizations increasingly adapt Large Language Models (LLMs) from public repositories such as HuggingFace to downstream tasks. Prior work sho

EgoIntent: A Pre-Outcome Micro-Step Benchmark for Understanding What, Why, and Next

arXiv:2603.12147v2 Announce Type: replace Abstract: Egocentric video provides a natural modality for studying human behavior, but conventional visual understanding captures mainly observable scenes, o

Emergence Invariance: From Symbolized Thought to Interface Refinement

arXiv:2608.01548v1 Announce Type: cross Abstract: Language can be viewed as a formalized subset of thought: a consequence-governed symbolic structure projected from wider situated cognition. Large lan

ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs

arXiv:2608.01979v1 Announce Type: cross Abstract: Visual token pruning reduces the inference cost of multimodal large language models, but a fixed token ratio is poorly matched to text-rich inputs. In

EulerLoRA: Rank-Driven Jump Dynamics for Calibrated Parameter-Efficient Fine-Tuning

arXiv:2608.01142v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) enables parameter-efficient fine-tuning, but standard LoRA produces a single deterministic model and does not directly suppor

Evaluating VLMs on Multimodal Aristotelian Persuasion Tasks

arXiv:2608.01238v1 Announce Type: new Abstract: Vision Language Models (VLMs) have demonstrated exceptional performance across various tasks. However, they have not yet been thoroughly evaluated on mo

Event ActivityNet: A Large-Scale Simulated-Event Benchmark for Untrimmed Action Understanding

arXiv:2608.01948v1 Announce Type: new Abstract: Long-horizon event-based action understanding remains underexplored because existing datasets largely comprise short, trimmed clips, while collecting na