Search: “context”

AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models

arXiv:2405.16240v3 Announce Type: replace Abstract: In this paper, we introduce analytic federated learning (AFL), a new training paradigm that brings analytical (i.e., closed-form) solutions to the f

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AI generates well-liked but templatic empathic responses

DGX agent

arXiv:2604.08479v1 Announce Type: new Abstract: Recent research shows that greater numbers of people are turning to Large Language Models (LLMs) for emotional support, and that people rate LLM respons

applicationsarxiv-cs-cl

10 Apr 2026

Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference

arXiv:2604.08133v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become a dominant architecture for scaling large language models due to their sparse activation mechanism. However, the s

AutoReproduce: Automatic AI Experiment Reproduction with Paper Lineage

arXiv:2505.20662v3 Announce Type: replace Abstract: Efficient reproduction of research papers is pivotal to accelerating scientific progress. However, the increasing complexity of proposed methods oft

Before We Trust Them: Decision-Making Failures in Navigation of Foundation Models

arXiv:2601.05529v5 Announce Type: replace Abstract: High success rates on navigation-related tasks do not necessarily translate into reliable decision making by foundation models. To examine this gap,

Hardware

CodecSight: Leveraging Video Codec Signals for Efficient Streaming VLM Inference

arXiv:2604.06036v3 Announce Type: replace-cross Abstract: Video streaming analytics is a crucial workload for vision-language model serving, but the high cost of multimodal inference limits scalabilit

hardwarearxiv-cs-cv

CompoDistill: Attention Distillation for Compositional Reasoning in Multimodal LLMs

arXiv:2510.12184v2 Announce Type: replace Abstract: Recently, efficient Multimodal Large Language Models (MLLMs) have gained significant attention as a solution to their high computational complexity,

applicationsarxiv-cs-cv

CubeGraph: Efficient Retrieval-Augmented Generation for Spatial and Temporal Data

arXiv:2604.06616v1 Announce Type: cross Abstract: Hybrid queries combining high-dimensional vector similarity search with spatio-temporal filters are increasingly critical for modern retrieval-augment

applicationsarxiv-cs-ai

Local Ai

Data Selection for Multi-turn Dialogue Instruction Tuning

arXiv:2604.07892v1 Announce Type: new Abstract: Instruction-tuned language models increasingly rely on large multi-turn dialogue corpora, but these datasets are often noisy and structurally inconsiste

local-aiarxiv-cs-cl

DBMF: A Dual-Branch Multimodal Framework for Out-of-Distribution Detection

arXiv:2604.08261v1 Announce Type: new Abstract: The complex and dynamic real-world clinical environment demands reliable deep learning (DL) systems. Out-of-distribution (OOD) detection plays a critica

applicationsarxiv-cs-cv

DHFP-PE: Dual-Precision Hybrid Floating Point Processing Element for AI Acceleration

arXiv:2604.04507v2 Announce Type: replace-cross Abstract: The rapid adoption of low-precision arithmetic in artificial intelligence and edge computing has created a strong demand for energy-efficient

researcharxiv-cs-ro

Direct Segmentation without Logits Optimization for Training-Free Open-Vocabulary Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.07723v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment arbitrary category regions in images using open-vocabulary prompts, necessitating that exis

Distributed Multi-Layer Editing for Rule-Level Knowledge in Large Language Models

arXiv:2604.08284v1 Announce Type: new Abstract: Large language models store not only isolated facts but also rules that support reasoning across symbolic expressions, natural language explanations, an

Safety

Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook

arXiv:2604.06210v2 Announce Type: cross Abstract: As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks fac

safetyarxiv-cs-ai

Draw-In-Mind: Rebalancing Designer-Painter Roles in Unified Multimodal Models Benefits Image Editing

arXiv:2509.01986v4 Announce Type: replace-cross Abstract: In recent years, integrating multimodal understanding and generation into a single unified model has emerged as a promising paradigm. While th

Efficient Quantization of Mixture-of-Experts with Theoretical Generalization Guarantees

arXiv:2604.06515v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) allows scaling of language and vision models efficiently by activating only a small subset of experts per input. While

researcharxiv-cs-ai

Emotion Concepts and their Function in a Large Language Model

arXiv:2604.07729v1 Announce Type: cross Abstract: Large language models (LLMs) sometimes appear to exhibit emotional reactions. We investigate why this is the case in Claude Sonnet 4.5 and explore imp

Entropy-Gradient Grounding: Training-Free Evidence Retrieval in Vision-Language Models

arXiv:2604.08456v1 Announce Type: cross Abstract: Despite rapid progress, pretrained vision-language models still struggle when answers depend on tiny visual details or on combining clues spread acros

researcharxiv-cs-cl

EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering

arXiv:2603.11703v2 Announce Type: replace Abstract: We introduce EvoFlows, a variable-length protein sequence-to-sequence modeling approach designed for protein engineering. Existing protein language

Agents

Exploring Plan Space through Conversation: An Agentic Framework for LLM-Mediated Explanations in Planning

arXiv:2603.02070v2 Announce Type: replace-cross Abstract: When automating plan generation for a real-world sequential decision problem, the goal is often not to replace the human planner, but to facil

agentsarxiv-cs-cl

FBS: Modeling Native Parallel Reading inside a Transformer

arXiv:2601.21708v2 Announce Type: replace Abstract: Large language models (LLMs) excel across many tasks, yet inference is still dominated by strictly token-by-token autoregression. Existing accelerat

researcharxiv-cs-ai

Hardware

HAWK: Head Importance-Aware Visual Token Pruning in Multimodal Models

arXiv:2604.07812v1 Announce Type: new Abstract: In multimodal large language models (MLLMs), the surge of visual tokens significantly increases the inference time and computational overhead, making th

hardwarearxiv-cs-cv

Initialisation Determines the Basin: Efficient Codebook Optimisation for Extreme LLM Quantization

arXiv:2604.08118v1 Announce Type: new Abstract: Additive quantization enables extreme LLM compression with O(1) lookup-table dequantization, making it attractive for edge deployment. Yet at 2-bit prec

k-Maximum Inner Product Attention for Graph Transformers and the Expressive Power of GraphGPS

arXiv:2604.03815v2 Announce Type: replace-cross Abstract: Graph transformers have shown promise in overcoming limitations of traditional graph neural networks, such as oversquashing and difficulties i

Low-Rank Key Value Attention

arXiv:2601.11471v3 Announce Type: replace Abstract: The key-value (KV) cache is a primary memory bottleneck in Transformers. We propose Low-Rank Key-Value (LRKV) attention, which reduces KV cache memo

Safety

MemReader: From Passive to Active Extraction for Long-Term Agent Memory

arXiv:2604.07877v1 Announce Type: new Abstract: Long-term memory is fundamental for personalized and autonomous agents, yet populating it remains a bottleneck. Existing systems treat memory extraction

safetyarxiv-cs-cl

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting

arXiv:2604.06473v1 Announce Type: new Abstract: Multivariate forecasting with Transformers faces a core scalability challenge: modeling cross-channel dependencies via attention compounds attention's q

Agents

Mina: A Multilingual LLM-Powered Legal Assistant Agent for Bangladesh for Empowering Access to Justice

arXiv:2511.08605v3 Announce Type: replace Abstract: Bangladesh's low-income population faces major barriers to affordable legal advice due to complex legal language, procedural opacity, and high costs

agentsarxiv-cs-cl

Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clustering

arXiv:2604.07085v1 Announce Type: new Abstract: In electronic health records (EHRs), clustering patients and distinguishing disease subtypes are key tasks to elucidate pathophysiology and aid clinical

applicationsarxiv-cs-lg

MM-MoralBench: A MultiModal Moral Evaluation Benchmark for Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2412.20718v2 Announce Type: replace Abstract: The rapid integration of Large Vision-Language Models (LVLMs) into critical domains necessitates comprehensive moral evaluation to ensure their alig

Local Ai

MoBiE: Efficient Inference of Mixture of Binary Experts under Post-Training Quantization

arXiv:2604.06798v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) based large language models (LLMs) offer strong performance but suffer from high memory and computation costs. Weight binariz

local-aiarxiv-cs-ai

Modernizing Amdahl's Law: How AI Scaling Laws Shape Computer Architecture

arXiv:2603.20654v4 Announce Type: replace-cross Abstract: Classical Amdahl's Law conceptualized the limit of speedup for an era of fixed serial-parallel decomposition and homogeneous replication. Mode

researcharxiv-cs-ai

MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations

arXiv:2603.28253v2 Announce Type: replace-cross Abstract: Time series forecasting is vital across many domains, yet existing models struggle with fixed-length inputs and inadequate multi-scale modelin

applicationsarxiv-cs-ai

Agents

NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous Navigation

arXiv:2406.13086v2 Announce Type: replace Abstract: Lightweight autonomous unmanned aerial vehicles (UAV) are emerging as a central component of a broad range of applications. However, autonomous navi

agentsarxiv-cs-ro

ODYN: An All-Shifted Non-Interior-Point Method for Quadratic Programming in Robotics and AI

arXiv:2602.16005v2 Announce Type: replace-cross Abstract: We introduce ODYN, a novel all-shifted primal-dual non-interior-point quadratic programming (QP) solver designed to efficiently handle challen

OmniTabBench: Mapping the Empirical Frontiers of GBDTs, Neural Networks, and Foundation Models for Tabular Data at Scale

arXiv:2604.06814v1 Announce Type: cross Abstract: While traditional tree-based ensemble methods have long dominated tabular tasks, deep neural networks and emerging foundation models have challenged t

On Integrating Resilience and Human Oversight into LLM-Assisted Modeling Workflows for Digital Twins

arXiv:2603.25898v2 Announce Type: replace-cross Abstract: LLM-assisted modeling holds the potential to rapidly build executable Digital Twins of complex systems from only coarse descriptions and senso

OpenTrack3D: Towards Accurate and Generalizable Open-Vocabulary 3D Instance Segmentation

arXiv:2512.03532v2 Announce Type: replace Abstract: Generalizing open-vocabulary 3D instance segmentation (OV-3DIS) to diverse, unstructured, and mesh-free environments is crucial for robotics and AR/

researcharxiv-cs-cv

PANC: Prior-Aware Normalized Cut via Anchor-Augmented Token Graphs

arXiv:2602.06912v2 Announce Type: replace Abstract: Unsupervised segmentation from self-supervised ViT patches holds promise but lacks robustness: multi-object scenes confound saliency cues, and low-s

researcharxiv-cs-cv

PASK: Toward Intent-Aware Proactive Agents with Long-Term Memory

arXiv:2604.08000v1 Announce Type: cross Abstract: Proactivity is a core expectation for AGI. Prior work remains largely confined to laboratory settings, leaving a clear gap in real-world proactive age

Production-Ready Automated ECU Calibration using Residual Reinforcement Learning

arXiv:2604.07059v1 Announce Type: new Abstract: Electronic Control Units (ECUs) have played a pivotal role in transforming motorcars of yore into the modern vehicles we see on our roads today. They ac

applicationsarxiv-cs-lg

Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression

arXiv:2604.04988v1 Announce Type: cross Abstract: Modern deployment often requires trading accuracy for efficiency under tight CPU and memory constraints, yet common compression proxies such as parame

Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning

arXiv:2508.07299v2 Announce Type: replace-cross Abstract: The effectiveness of unlabeled data in Semi/Self-Supervised Learning (SSL) depends on appropriate assumptions for specific scenarios, thereby

Reasoning-Based Refinement of Unsupervised Text Clusters with LLMs

arXiv:2604.07562v1 Announce Type: new Abstract: Unsupervised methods are widely used to induce latent semantic structure from large text collections, yet their outputs often contain incoherent, redund

applicationsarxiv-cs-cl

Restoring Heterogeneity in LLM-based Social Simulation: An Audience Segmentation Approach

arXiv:2604.06663v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to simulate social attitudes and behaviors, offering scalable 'silicon samples' that can approximat

Rethinking Data Mixing from the Perspective of Large Language Models

arXiv:2604.07963v1 Announce Type: new Abstract: Data mixing strategy is essential for large language model (LLM) training. Empirical evidence shows that inappropriate strategies can significantly redu

researcharxiv-cs-cl

Hardware

RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs

arXiv:2510.19225v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become essential for unlocking advanced reasoning capabilities in large language models (LLMs). RL workflows i

hardwarearxiv-cs-lg

Safety

RoboAgent: Chaining Basic Capabilities for Embodied Task Planning

arXiv:2604.07774v1 Announce Type: cross Abstract: This paper focuses on embodied task planning, where an agent acquires visual observations from the environment and executes atomic actions to accompli

safetyarxiv-cs-cv