All entries

A Practice of Post-Training on Llama-3 70B with Optimal Selection of Additional Language Mixture Ratio

model-releasesarxiv-cs-ai

arXiv:2409.06624v4 Announce Type: replace-cross Abstract: Large Language Models (LLM) often need to be Continual Pre-Trained (CPT) to obtain unfamiliar language skills or adapt to new domains. The hug

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

A Priori Sampling of Transition States with Guided Diffusion

DGX agent

arXiv:2603.25980v2 Announce Type: replace-cross Abstract: Transition states, the first-order saddle points on the potential energy surfaces, govern the kinetics and mechanisms of chemical reactions an

researcharxiv-cs-lg

30 Apr 2026

A projection-based framework for gradient-free and parallel learning

arXiv:2506.05878v2 Announce Type: replace Abstract: We present a feasibility-seeking approach to neural network training. This mathematical optimization framework is distinct from conventional gradien

hardwarearxiv-cs-lg

A Quantitative Confirmation of the Currier Language Distinction

arXiv:2604.25979v1 Announce Type: cross Abstract: We present a quantitative analysis of character-pair substitution ratios in the Voynich manuscript, testing whether Currier's A/B language distinction

researcharxiv-cs-cl

A Randomized PDE Energy driven Iterative Framework for Efficient and Stable PDE Solutions

arXiv:2604.25943v1 Announce Type: cross Abstract: Efficient and stable solution of partial differential equations (PDEs) is central to scientific and engineering applications, yet existing numerical s

A Scaled Three-Vehicle Platooning Platform

arXiv:2604.25963v1 Announce Type: new Abstract: Vehicle platooning has attracted increasing attention as a promising approach to improve traffic efficiency, energy consumption, and roadway safety thro

safetyarxiv-cs-ro

A Scoping Review of LLM-as-a-Judge in Healthcare and the MedJUDGE Framework

arXiv:2604.25933v1 Announce Type: cross Abstract: As large language models (LLMs) increasingly generate and process clinical text, scalable evaluation has become critical. LLM-as-a-Judge (LaaJ), which

A Self-Calibrating Framework for Analog Circuit Sizing Using LLM-Derived Analytical Equations

arXiv:2604.07387v2 Announce Type: replace-cross Abstract: We present a design automation framework for analog circuit sizing that produces calibrated, topology-specific analytical equations from raw c

A self-evolving agent for explainable diagnosis of DFT-experiment band-gap mismatch

model-releasesarxiv-cs-ai

arXiv:2604.26703v1 Announce Type: cross Abstract: Standard density functional theory (DFT) routinely misclassifies the electronic ground state of correlated and structurally complex compounds, predict

Agents

A Survey of Multi-Agent Deep Reinforcement Learning with Graph Neural Network-Based Communication

arXiv:2604.25972v1 Announce Type: cross Abstract: In multi-agent reinforcement learning (MARL), the integration of a communication mechanism, allowing agents to better learn to coordinate their action

agentsarxiv-cs-ai

A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models

arXiv:2510.08049v3 Announce Type: replace-cross Abstract: Although Large Language Models (LLMs) exhibit advanced reasoning ability, conventional alignment remains largely dominated by outcome reward m

A Survey of Safe Reinforcement Learning and Constrained MDPs: A Technical Survey on Single-Agent and Multi-Agent Safety

arXiv:2505.17342v2 Announce Type: replace Abstract: Safe Reinforcement Learning (SafeRL) is the subfield of reinforcement learning that explicitly deals with safety constraints during the learning and

safetyarxiv-cs-lg

A Survey on the Safety and Security Threats of Computer-Using Agents: JARVIS or Ultron?

arXiv:2505.10924v4 Announce Type: replace-cross Abstract: Recently, AI-driven interactions with computing devices have advanced from basic prototype tools to sophisticated, LLM-based systems that emul

A Systematic Comparison of Prompting and Multi-Agent Methods for LLM-based Stance Detection

arXiv:2604.26319v1 Announce Type: new Abstract: Stance detection identifies the attitude of a text author toward a given target. Recent studies have explored various LLM-based strategies for this task

A Toolkit for Detecting Spurious Correlations in Speech Datasets

arXiv:2604.26676v1 Announce Type: cross Abstract: We introduce a toolkit for uncovering spurious correlations between recording characteristics and target class in speech datasets. Spurious correlatio

Tutorials

A Virtual Mechanical Interaction Layer Enables Resilient Human-to-Robot Object Handovers

arXiv:2511.19543v2 Announce Type: replace Abstract: Object handover is a common form of interaction that is widely present in collaborative tasks. However, achieving it efficiently remains a challenge

tutorialsarxiv-cs-ro

Accelerating RL Post-Training Rollouts via System-Integrated Speculative Decoding

arXiv:2604.26779v1 Announce Type: cross Abstract: RL post-training of frontier language models is increasingly bottlenecked by autoregressive rollout generation, making rollout acceleration a central

safetyarxiv-cs-cl

ACPO: Anchor-Constrained Perceptual Optimization for Diffusion Models with No-Reference Quality Guidance

arXiv:2604.26348v1 Announce Type: cross Abstract: Diffusion models have achieved remarkable success in image generation, yet their training is predominantly driven by full-reference objectives that en

Local Ai

Action Hints: Semantic Typicality and Context Uniqueness for Generalizable Skeleton-based Video Anomaly Detection

arXiv:2509.11058v2 Announce Type: replace Abstract: Zero-Shot Video Anomaly Detection (ZS-VAD) requires temporally localizing anomalies without target domain training data, which is a crucial task due

local-aiarxiv-cs-cv

AdaFRUGAL: Adaptive Memory-Efficient Training with Dynamic Control

arXiv:2601.11568v2 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) is highly memory-intensive due to optimizer state overhead. The FRUGAL framework mitigates this with gra

hardwarearxiv-cs-ai

AdaMem: Adaptive User-Centric Memory for Long-Horizon Dialogue Agents

arXiv:2603.16496v2 Announce Type: replace Abstract: Large language model (LLM) agents increasingly rely on external memory to support long-horizon interaction, personalized assistance, and multi-step

Adaptive and Fine-grained Module-wise Expert Pruning for Efficient LoRA-MoE Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2604.26340v1 Announce Type: new Abstract: LoRA-MoE has emerged as an effective paradigm for parameter-efficient fine-tuning, combining the low training cost of LoRA with the increased adaptation

Local Ai

Adaptive Layerwise Perturbation: Unifying Off-Policy Corrections for LLM RL

arXiv:2603.19470v2 Announce Type: replace-cross Abstract: Off-policy problems such as policy staleness and training--inference mismatch have become a major bottleneck for training stability and furthe

local-aiarxiv-cs-ai

Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2508.19900v2 Announce Type: replace Abstract: Offline reinforcement learning (RL) enables learning effective policies from fixed datasets without any environment interaction. Existing methods ty

Adaptive Transform Coding for Semantic Compression

arXiv:2604.26492v1 Announce Type: cross Abstract: Visual data compression is shifting from human-centered reconstruction to machine-oriented representation coding. In this setting, an image is often m

researcharxiv-cs-cv

Addressing Performance Saturation for LLM RL via Precise Entropy Curve Control

arXiv:2604.26326v1 Announce Type: cross Abstract: Reinforcement learning (RL) has unlocked complex reasoning abilities in large language models (LLMs). However, most RL algorithms suffer from performa

researcharxiv-cs-cl

Advancing multi-site emission control: A physics-informed transfer learning framework with mixture of experts for carbon-pollutant synergy

arXiv:2604.26571v1 Announce Type: new Abstract: Municipal solid waste incineration is increasingly central to urban waste management, yet its sustainability benefit depends on controlling carbon emiss

researcharxiv-cs-lg

Adversarial Robustness of NTK Neural Networks

arXiv:2604.25965v1 Announce Type: cross Abstract: Deep learning models are widely deployed in safety-critical domains, but remain vulnerable to adversarial attacks. In this paper, we study the adversa

safetyarxiv-cs-lg

Affective Flow Language Model for Emotional Support Conversation

model-releasesarxiv-cs-ai

arXiv:2602.08826v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been widely applied to emotional support conversation (ESC). However, complex multi-turn support remains cha

Applications

AfrIFact: Cultural Information Retrieval, Evidence Extraction and Fact Checking for African Languages

arXiv:2604.00706v2 Announce Type: replace Abstract: Assessing the veracity of a claim made online is a complex and important task with real-world implications. When these claims are directed at commun

applicationsarxiv-cs-cl

Agents

AGEL-Comp: A Neuro-Symbolic Framework for Compositional Generalization in Interactive Agents

arXiv:2604.26522v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents exhibit systemic failures in compositional generalization, limiting their robustness in interactive environments

agentsarxiv-cs-ai

Agentic Search in the Wild: Intents and Trajectory Dynamics from 14M+ Real Search Requests

arXiv:2601.17617v3 Announce Type: replace-cross Abstract: LLM-powered search agents are increasingly being used for multi-step information seeking tasks, yet the IR community lacks empirical understan

AHASD: Asynchronous Heterogeneous Architecture for LLM Adaptive Drafting Speculative Decoding on Mobile Devices

arXiv:2604.25326v2 Announce Type: replace-cross Abstract: Speculative decoding enhances the inference efficiency of large language models (LLMs) by generating drafts using a small draft language model

hardwarearxiv-cs-ai

AirZoo: A Unified Large-Scale Dataset for Grounding Aerial Geometric 3D Vision

model-releasesarxiv-cs-cv

arXiv:2604.26567v1 Announce Type: new Abstract: Despite the rapid progress in data-driven 3D vision, aerial geometric 3D vision remains a formidable challenge due to the severe scarcity of large-scale

Applications

AlphaJet: Automated Conceptual Aircraft Synthesis via Disentangled Generative Priors and Topology-Preserving Evolutionary Search

arXiv:2604.26337v1 Announce Type: new Abstract: Conceptual aircraft design is traditionally an expert-mediated iterative process in which a human designer proposes a configuration, runs low-order phys

applicationsarxiv-cs-lg

Agents

Alter-Art: Exploring Embodied Artistic Creation through a Robot Avatar

arXiv:2604.26473v1 Announce Type: new Abstract: As with every emerging technology, new tools in the hands of artists reshape the nature of artwork creation. Current frameworks for robotics in arts dep

agentsarxiv-cs-ro

AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving

arXiv:2604.26103v1 Announce Type: cross Abstract: All current LLM serving systems place the GPU at the center, from production-level attention-FFN disaggregation to NVIDIA's Rubin GPU-LPU heterogeneou

hardwarearxiv-cs-ai

Applications

Analysing Lightweight Large Language Models for Biomedical Named Entity Recognition on Diverse Ouput Formats

arXiv:2604.25920v1 Announce Type: cross Abstract: Despite their strong linguistic capabilities, Large Language Models (LLMs) are computationally demanding and require substantial resources for fine-tu

applicationsarxiv-cs-ai

Anchored Confabulation: Partial Evidence Non-Monotonically Amplifies Confident Hallucination in LLMs

arXiv:2604.25931v1 Announce Type: new Abstract: We identify a previously unknown calibration property of large language models: providing one confirmed intermediate fact toward a multi-step reasoning

researcharxiv-cs-cl

AnimateAnyMesh++: A Flexible 4D Foundation Model for High-Fidelity Text-Driven Mesh Animation

arXiv:2604.26917v1 Announce Type: new Abstract: Recent advances in 4D content generation have attracted increasing attention, yet creating high-quality animated 3D models remains challenging due to th

researcharxiv-cs-cv

Apriori-based Analysis of Learned Helplessness in Mathematics Tutoring: Behavioral Patterns by Level, Intervention, and Outcome

arXiv:2604.26237v1 Announce Type: new Abstract: This study applied the Apriori algorithm to analyze behavioral interaction patterns associated with learned helplessness (LH) in mathematics tutoring sy

Are Data Augmentation and Segmentation Always Necessary? Insights from COVID-19 X-Rays and a Methodology Thereof

arXiv:2604.26437v1 Announce Type: new Abstract: Purpose: Rapid and reliable diagnostic tools are crucial for managing respiratory diseases like COVID-19, where chest X-ray analysis coupled with artifi

researcharxiv-cs-cv

Assessing the Utility of Volumetric Motion Fields for Radar-based Precipitation Nowcasting with Physics-informed Deep Learning

arXiv:2603.13589v2 Announce Type: replace-cross Abstract: Estimating motion from spatiotemporal geoscientific data is a fundamental component of many environmental modeling and forecasting tasks. In t

Associative-State Universal Transformers: Sparse Retrieval Meets Structured Recurrence

arXiv:2604.25930v1 Announce Type: new Abstract: We study whether a structured recurrent state can serve as a compact associative backbone for language modeling while still supporting exact retrieval.

Asymptotically Robust Learning-Augmented Algorithms for Preemptive FIFO Buffer Management

arXiv:2604.26349v1 Announce Type: cross Abstract: We present a learning-augmented online algorithm for the preemptive FIFO buffer management problem, where packets arrive online to a finite-capacity b

researcharxiv-cs-lg

Asynchronous Federated Unlearning with Invariance Calibration for Medical Imaging

arXiv:2604.26809v1 Announce Type: new Abstract: Federated Unlearning (FU) is an emerging paradigm in Federated Learning (FL) that enables participating clients to fully remove their contributions from

researcharxiv-cs-lg

ATLAS: An Annotation Tool for Long-horizon Robotic Action Segmentation

arXiv:2604.26637v1 Announce Type: cross Abstract: Annotating long-horizon robotic demonstrations with precise temporal action boundaries is crucial for training and evaluating action segmentation and

Atomic-Probe Governance for Skill Updates in Compositional Robot Policies

arXiv:2604.26689v1 Announce Type: cross Abstract: Skill libraries in deployed robotic systems are continually updated through fine-tuning, fresh demonstrations, or domain adaptation, yet existing type