Search: “framework”

Sustaining Plasticity via Learnable Wavelet Activations in Continual Learning

arXiv:2608.12874v1 Announce Type: new Abstract: Plasticity loss has emerged as a critical challenge in continual learning that significantly hinders the acquisition of sequential tasks. While optimizi

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Research

Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion

DGX agent

arXiv:2608.13457v1 Announce Type: new Abstract: Generating crystals has recently attracted significant interest due to their broad applications in materials science. However, existing generative model

researcharxiv-cs-lg

14 Aug 2026

SynAct: A Reasoning-Acting Large Language Model Agent for Adaptive Synthesis Optimization

arXiv:2608.12751v1 Announce Type: cross Abstract: Logic synthesis transforms RTL designs into gate-level netlists, where PPA results are highly sensitive to the choice of optimization commands, making

agentsarxiv-cs-ai

SynWeaver: Website-Prior Task and Trajectory Co-Synthesis for Web Agents

arXiv:2608.12429v1 Announce Type: cross Abstract: Web agents often struggle to generalize to unseen websites because they lack website-specific supervision. Recent exploration-based data synthesis met

Teach the Magnitude, Not the Direction: Verifier-Bounded Credit Assignment for Multi-Turn Multi-step LLM Agents

arXiv:2608.13179v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) offers a verifier-bounded performance ceiling for training multi-turn tool-use agents, yet its tra

The Time Value of Evolution

arXiv:2608.13297v1 Announce Type: new Abstract: In evolutionary search, a weak child can be a valuable ancestor that makes high-fitness regions reachable. Immediate-return control is blind to this del

Topology-Unified 2D Pose Estimation across Intact, Residual and Prosthetic Limbs

arXiv:2608.13047v1 Announce Type: new Abstract: Driven by the availability of large-scale datasets, Human Pose Estimation (HPE) plays a critical role in numerous downstream tasks. However, mainstream

Applications

Towards Sparsely Annotated Open-World Object Detection

arXiv:2608.12714v1 Announce Type: new Abstract: Real-world object detection operates under ambiguous supervision, where unlabeled regions may correspond to missing annotations of known objects or genu

applicationsarxiv-cs-cv

Training Under Challenge: Executable Certificates and Challenge-Closed Optimality for Neural Networks

arXiv:2608.12655v1 Announce Type: new Abstract: A flat training curve does not reveal whether a neural network has reached a global optimum, is locally trapped, is representation-limited, or is mismat

researcharxiv-cs-lg

TraVEL: Trajectory-Guided Video Embedding Learning for Driving-Video Retrieval

arXiv:2608.13495v1 Announce Type: new Abstract: Efficiently retrieving relevant clips from large-scale driving logs is essential for data curation, model development, and safety analysis. Structured a

Unifying Depth and Width Pruning for LLMs via Binary Knapsack Optimization

model-releasesarxiv-cs-cl

arXiv:2608.12953v1 Announce Type: new Abstract: Structured pruning is a promising approach for compressing large language models (LLMs), yet existing methods rely heavily on greedy heuristics that pro

Unmasking Conversational Bias in AI Multiagent Systems

arXiv:2501.14844v3 Announce Type: replace-cross Abstract: Detecting biases in the outputs produced by generative models is essential to reduce the potential risks associated with their application in

VOS-Agent: The 1st Place Solution for the 8th LSVOS Challenge (MOSEv2 Track)

arXiv:2608.12721v1 Announce Type: new Abstract: Complex video object segmentation requires robust target propagation under severe occlusion, disappearance and reappearance. Although SAM3 provides stro

agentsarxiv-cs-cv

vToken: Token-Level Virtualization for Reclaimable KV Caches

arXiv:2608.13263v1 Announce Type: new Abstract: Large language model serving faces a critical memory bottleneck: the KV cache grows with sequence length and batch size. PagedAttention uses fixed-size

Wasserstein Filtering: A Sample Selection Method for Robust Distribution Learning

model-releasesarxiv-cs-lg

arXiv:2608.13418v1 Announce Type: cross Abstract: Given a dataset where a portion of the samples are contaminated, our goal is to recover the underlying clean population distribution. To this end, we

What Drives LLM Self-Reflection? A Controlled Ablation of Uncertainty Routing in Armed Conflict Forecasting

arXiv:2608.12322v1 Announce Type: cross Abstract: Self-reflection is widely assumed to improve LLM reasoning, yet which component drives the gain remains poorly understood. We present a controlled six

A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement

model-releasesarxiv-cs-cl

arXiv:2608.12269v1 Announce Type: new Abstract: Public procurement involves the allocation of substantial financial resources; therefore, continuous oversight through audits, controls, and monitoring

A Forced-Structure Reduction and Verifiable Bounds for Conway's 99-Graph

arXiv:2608.11211v1 Announce Type: new Abstract: Conway's 99-graph problem asks whether a strongly regular graph with parameters srg(99,14,1,2) exists. We report a systematic, fully reproducible attack

agentsarxiv-cs-ai

A New First-Order Meta-Learning Algorithm with Convergence Guarantees

arXiv:2409.03682v2 Announce Type: replace Abstract: Learning new tasks by leveraging prior experience is a fundamental trait of intelligent systems. While Model-Agnostic Meta-Learning (MAML) is a lead

Anti-Shortcut Distillation via Temporal Negative Knowledge Transfer

arXiv:2608.11789v1 Announce Type: new Abstract: Knowledge distillation (KD) trains a compact student by attracting it towards a converged teacher. It is silent about which directions the teacher itsel

safetyarxiv-cs-cv

APEX: Adaptive Expert Prefetching for Memory-Efficient Edge MoE Inference

arXiv:2608.11688v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models are attractive for edge deployment because they provide high model capacity while activating only a small subset of pa

Apodex Discovery: Reality Benchmarks and Environments for Evaluating and Building Discoverative Artificial Intelligence

arXiv:2608.11341v1 Announce Type: new Abstract: Apollo did not reach the Moon merely because its engineers could solve difficult equations. It succeeded by turning a distant ambition into a mission ar

Automated Borehole Core Analysis with Report-Derived Weak Labels and Supervised Crack Segmentation

arXiv:2608.12252v1 Announce Type: new Abstract: Borehole archives commonly contain core tray photographs and corresponding digital log reports, but no native pixel-level crack annotations. We investig

researcharxiv-cs-cv

Autonomous Telerehabilitation via Skeletal Motion Prediction and Joint-Level Performance Assessment

arXiv:2608.12145v1 Announce Type: new Abstract: Autonomous rehabilitation systems must not only recognize human motion but also provide structured feedback to support users without continuous therapis

agentsarxiv-cs-cv

Avatar-Forever: Decoupled Parallel Training for High-Quality Real-Time Infinite Avatars

arXiv:2608.12107v1 Announce Type: new Abstract: Existing streaming video systems often rely on sequential, distillation-centered training pipelines to enable few-step long-video generation. However, t

Backdoor Decontamination Dynamics in LLM Agents

arXiv:2608.11295v1 Announce Type: cross Abstract: Open-weight LLM agents are vulnerable to backdoors installed during fine-tuning, which may be undetectable if the trigger conditions are never met dur

Backtrader-Bench: Benchmarking LLM Agents on Algorithmic Trading with Self-Generated MCQs

arXiv:2608.11232v1 Announce Type: cross Abstract: Evaluating LLM coding agents in algorithmic trading is difficult because static benchmarks risk data contamination and numerical backtest outputs requ

Behavior and Representation in Open-Weight Large Language Models for Combinatorial Optimization: From Feature Extraction to Algorithm Selection

arXiv:2512.13374v2 Announce Type: replace Abstract: Recent advances in Large Language Models (LLMs) open new perspectives for automation in optimization, yet little is known about whether their intern

Beyond Parameter Space: NTK-Guided Personalized Aggregation for Robust Federated Learning

model-releasesarxiv-cs-lg

arXiv:2608.12108v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative model training across distributed clients while keeping data local. A central challenge is determining whi

Causal Agent based on Large Language Model

arXiv:2408.06849v3 Announce Type: replace Abstract: The large language model (LLM) has achieved significant success across various domains. However, the inherent complexity of causal problems and caus

CLAIM: Leading Open-domain Active Clarification of Large Language Models with Uncertainty Measurement

arXiv:2608.11631v1 Announce Type: new Abstract: In open-domain human-computer interaction scenarios, large language models (LLMs) frequently encounter user queries that are ambiguous or incomplete. In

Claim-Level Reliability Assessment for Efficient Test-Time Reasoning

arXiv:2608.11994v1 Announce Type: new Abstract: We propose claim-level falsification as a principle for test-time scaling and instantiate it through Claim-Level Reliability Assessment (CLR), a trainin

CLEAR: Class-wise Expert Aggregation with Structured Sampling for Long-Tailed Classification

arXiv:2608.11287v1 Announce Type: cross Abstract: Long-tailed classification poses a reliability challenge because models trained on imbalanced data are unevenly reliable across frequent and underrepr

CoAdapt-GUI: Joint Workflow Context and Policy Adaptation for Unseen GUI Applications

arXiv:2608.11588v1 Announce Type: new Abstract: Mobile GUI agents remain brittle when deployed to applications absent from source training. We study novel-app generalization under a limited target int

CoDiR: Confidence-Guided Diffusion Refinement for Semi-Supervised Histopathology Segmentation

arXiv:2608.11807v1 Announce Type: new Abstract: Semi-supervised histopathology segmentation is challenging due to scarce annotations and unreliable pseudo-labels in ambiguous gland regions. To address

COGENT: Counterfactual Gaussian Explanations for Volumetric Medical Images

arXiv:2608.11422v1 Announce Type: new Abstract: Explainability is essential for deploying deep learning models in high-stakes medical applications. Existing explainability methods for volumetric imagi

Commonsense on Demand: Generating and Selectively Integrating Commonsense Knowledge for Natural Language Inference

arXiv:2507.15100v3 Announce Type: replace-cross Abstract: Natural Language Inference (NLI) determines whether a premise entails, contradicts, or is neutral with respect to a hypothesis. The task is of

Credo: Declarative Control of LLM Pipelines via Beliefs and Policies

arXiv:2604.14401v2 Announce Type: replace Abstract: Agentic AI systems are becoming commonplace in domains that require long-lived, stateful decision-making in continuously evolving conditions. As suc

agentsarxiv-cs-ai

Defending against Model Extraction for GNNs with Model Reprogramming

arXiv:2608.11495v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) serve as the backbone for high-stakes applications in Machine-Learning-as-a-Service (MLaaS). Still, their black-box deploym

Local Ai

Diffusion-Based Data-Driven Assortment Optimization

arXiv:2608.11419v1 Announce Type: new Abstract: Assortment optimization is a fundamental problem in revenue management, typically addressed using parametric choice models such as the multinomial logit

local-aiarxiv-cs-lg

Diffusion Probe: Generated Image Result Prediction Using CNN Probes

arXiv:2602.23783v5 Announce Type: replace Abstract: Text-to-image (T2I) diffusion models lack an efficient mechanism for early quality assessment, leading to costly trial-and-error in multi-generation

agentsarxiv-cs-cv

Local Ai

Distillation of Foundation Models for Time-dependent PDEs

arXiv:2608.11937v1 Announce Type: new Abstract: Foundation models for time-dependent partial differential equations (PDEs) are trained on large and diverse collections of physical systems and can gene

local-aiarxiv-cs-lg

Do LLMs Take Care of Their Own? Similarity Signals Can Induce Cooperation

arXiv:2608.12125v1 Announce Type: cross Abstract: As LLM-based agents with user-instructed goals are becoming widely deployed, they increasingly encounter each other in strategic interactions, and fac

DreamFly: Causal Memory and Receding-Horizon Diffusion Planning for Aerial Vision-Language Navigation

arXiv:2608.12308v1 Announce Type: cross Abstract: Aerial vision-language navigation (VLN) requires an embodied agent to integrate visual evidence over time, plan future actions, and determine when it

DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation

arXiv:2507.14267v2 Announce Type: replace Abstract: Large language model (LLM) agents can execute long-horizon scientific workflows, but their numerical outputs are difficult to trust: agents lose con

Applications

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches

arXiv:2608.12007v1 Announce Type: cross Abstract: Consumer reviews play an important role in shaping brand perception and business strategies, particularly in service-driven industries such as retail

applicationsarxiv-cs-ai

Local Ai

EGM-Det: Entropy-Guided Multimodal Adaptive Fusion for UAV RGB-IR Object Detection

arXiv:2608.11685v1 Announce Type: new Abstract: Joint use of RGB and infrared (IR) imagery can improve UAV-view object detection, but most existing methods fuse multimodal features with static or fixe

local-aiarxiv-cs-cv

Energy-Aware Wind-Resilient Routing for Truck-Assisted Multi-UAV Delivery under Wind Uncertainty

arXiv:2608.11641v1 Announce Type: cross Abstract: Energy feasibility under wind uncertainty is a critical safety issue for low-altitude air-ground delivery. In truck-UAV systems, UAVs complete assigne

safetyarxiv-cs-ro