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Argument Quality Assessment with Large Language Models: A Pairwise Bradley-Terry Approach

arXiv:2605.28313v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in tasks related to reasoning and judgment. However, assessing the quality of arg

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Model Releases

Ariel-ML: Computing Parallelization with Embedded Rust for Neural Networks on Heterogeneous Multi-core Microcontrollers

DGX agent

arXiv:2512.09800v2 Announce Type: replace Abstract: Low-power microcontroller (MCU) hardware is currently evolving from single-core architectures to predominantly multi-core architectures. In parallel

model-releasesarxiv-cs-lg

28 May 2026

As Anthropic launches Claude Opus 4.8, it raises $65B in new funding

model-releasessiliconangle

Anthropic PBC today introduced a new large language model, Claude Opus 4.8, that’s significantly better than its predecessor at complex coding tasks. The company announced the LLM alongside another ma

Ask Now, Use Later: Benchmarking the Proactivity Gap in Long-Lived LLM Agents

arXiv:2605.28108v1 Announce Type: new Abstract: A long-lived LLM agent, such as OpenClaw, earns its value by acting on a user's preferences and constraints across sessions, not just the current reques

AssertLLM2: A Comprehensive LLM Benchmark for Assertion Generation from Design Specifications

arXiv:2605.27472v1 Announce Type: cross Abstract: Assertion-based verification (ABV) is a cornerstone of modern hardware design, yet manually translating design intent into formal SystemVerilog Assert

Assessing Factual Music Comprehension in Large Audio Language Models

arXiv:2511.05550v2 Announce Type: replace-cross Abstract: Large audio language models (LALMs) leverage multimodal representations to generate open-ended answers to natural language queries about audio

ASTRA: Communication-Efficient Acceleration for Multi-Device Transformer Inference

arXiv:2505.19342v2 Announce Type: replace-cross Abstract: Multi-device inference can reduce Transformer latency by parallelizing computation. However, existing methods require high inter-device bandwi

Asynchronous Remote Sensing Time-Series Fusion for Cloud Removal and Anytime Reconstruction

arXiv:2605.27726v1 Announce Type: new Abstract: Frequent cloud cover severely limits the usability of Sentinel-2 (S2) optical time series for Earth surface monitoring. Sentinel-1 (S1) SAR provides all

AsyncTool: Evaluating the Asynchronous Function Calling Capability under Multi-Task Scenarios

arXiv:2605.27995v1 Announce Type: new Abstract: Large language model (LLM)-based agents have shown strong capabilities in using external tools to solve complex tasks. However, existing evaluations oft

ATLAS: All-round Testing of Long-context Abilities across Scales

arXiv:2605.28079v1 Announce Type: new Abstract: Long-context language models now advertise context windows up to millions of tokens, yet evaluations typically report a single length or a narrow task f

Augmenting Attention with Exponentially Decaying Memory Improves Query-Aware KV Sparsity

arXiv:2605.28640v1 Announce Type: new Abstract: Efficient inference is critical for long-context language models, where attention computation and KV-cache access dominate the cost. Recent work RAT+, i

Automating Formal Verification with Agent-Guided Tree Search

arXiv:2605.27485v1 Announce Type: cross Abstract: Formal verification offers a path to provably correct software, but writing verified code remains expensive enough that the technique is rarely used i

Bandwidth-Efficient and Privacy-Preserving Edge-Cloud Many-to-Many Speech Translation

arXiv:2605.28642v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated significant potential for speech-to-text translation (S2TT). However, existing deployment par

Bayesian Optimization Parameter Tuning Framework for a Lyapunov Based Path Following Controller

model-releasesarxiv-cs-ro

arXiv:2512.12649v2 Announce Type: replace Abstract: Parameter tuning in real-world experiments is constrained by the limited evaluation budget available on hardware. The path-following controller stud

Benchmarking AI for low-resource contexts: Thinking beyond leaderboards

arXiv:2605.28508v1 Announce Type: new Abstract: Existing AI evaluation practices often fail to capture how systems actually perform in low-resource environments, where operational constraints shape us

Benchmarking and Mechanistic Analysis of Vision-Language Models for Cross-Depiction Assembly Instruction Alignment

arXiv:2604.00913v2 Announce Type: replace-cross Abstract: 2D assembly diagrams are often abstract and hard to follow, creating a need for intelligent assistants that can monitor progress, detect error

Benchmarking Fairness in Spiking Neural Networks: Data Bias, Spurious Features, and Hardware Effects

arXiv:2605.27407v1 Announce Type: cross Abstract: Evaluating fairness in Spiking Neural Networks (SNNs) demands rigorous benchmarks that reflect real-world complexities, yet existing assessments remai

Benchmarking Inductive Biases for Multivariate Time-Series Anomaly Detection with a Robust Multi-View Channel-Graph Detector

arXiv:2605.28103v1 Announce Type: new Abstract: We present a unified experiment, analysis, and benchmark study of multivariate time-series (MTS) anomaly detection. Ten family-representative detectors

Benchmarking Ultrasound Foundation Models for Fetal Plane Classification

arXiv:2605.27796v1 Announce Type: cross Abstract: Ultrasound is widely used in obstetric care due to its safety, accessibility, and real-time imaging. However, interpretation remains operator-dependen

Benchmarks are Not Enough: RAMP for Runtime Assessing of Agentic Models in Production Systems

arXiv:2605.27492v1 Announce Type: cross Abstract: LLM agents are rapidly evolving from coding assistants into autonomous software engineering systems. However, existing evaluation methodologies remain

BenGER: Benchmarking LLM Systems on Subsumption-Based Legal Reasoning in German Law

arXiv:2605.28183v1 Announce Type: cross Abstract: We introduce the BenGER (Benchmark for German Law) dataset for evaluating LLM systems on subsumption-based legal reasoning in German law. The BenGER d

Better Accuracies, Worse Reasoning: A Step-Level Audit of Medical Chain-of-Thought Distillation

arXiv:2605.28301v1 Announce Type: new Abstract: Chain-of-thought (CoT) distillation trains a smaller model to imitate a teacher's reasoning trace, but it is typically evaluated by final-answer metrics

Beyond being fast, LiteParse is designed to provide highly accurate, semantically coherent text for LLM use. We benchmarked every open-sourc…

model-releasesjerry-liu--x

Beyond being fast, LiteParse is designed to provide highly accurate, semantically coherent text for LLM use. We benchmarked every open-source, model-free PDF parser on LLM QA tasks - from PyPDF to PyM

Beyond Binary Moral Judgment: Modeling Ethical Pluralism in AI

arXiv:2605.28707v1 Announce Type: new Abstract: Critical decision-making in socially consequential spaces is increasingly involving AI systems at varying capacities. Yet, despite the ubiquity of auton

Beyond External Monitors: Enhancing Transparency of Large Language Models for Easier Monitoring

arXiv:2502.05242v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are becoming increasingly capable, but the mechanisms of their thinking and decision-making processes remain uncl

Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting

arXiv:2509.23074v3 Announce Type: replace-cross Abstract: In the era of increasingly complex AI models for time series forecasting, progress is often measured by marginal improvements on benchmark lea

Beyond Motion Primitives: Behavioral Activity Recognition from Head-Mounted IMU

arXiv:2605.27464v1 Announce Type: cross Abstract: AR smart glasses need continuous behavioral context to offer proactive assistance, yet their most practical always-on sensor, the head-mounted Inertia

Beyond One Path: Evaluating and Enhancing Divergent Thinking in Interactive LLM Agents

arXiv:2605.28465v1 Announce Type: new Abstract: Divergent thinking is a core dimension of creativity, yet existing evaluations of Large Language Models (LLMs) treat them as single-turn text generation

Bias Leaves a Gradient Trail: Label-Free Bias Identification via Gradient Probes on Concept Decompositions

arXiv:2605.28780v1 Announce Type: new Abstract: Vision classifiers can exploit spurious correlations, achieving high in-distribution accuracy yet failing under distribution shift. Existing approaches

Big migrations and refactors are some of a team's most important work, and the easiest to push off to a 'better time' since they'd tie up en…

model-releasesboris-cherny--x

Big migrations and refactors are some of a team's most important work, and the easiest to push off to a 'better time' since they'd tie up engineers for a quarter. With dynamic workflows, Claude can no

Bilinear Coordinate Alignment for Training-Free Task-Vector Transfer

arXiv:2605.28444v1 Announce Type: new Abstract: Fine-tuning large-scale pre-trained models is a recent prevalent paradigm for adapting general representations to specialized tasks. However, when a new

BioELX: Cross-lingual Biomedical Entity Linking via Alias-based Retrieval and LLM Ranking

arXiv:2605.27380v1 Announce Type: cross Abstract: Cross-lingual biomedical entity linking (BEL) maps mentions in any language to unique identifiers in a biomedical knowledge base (KB), supporting clin

BlazeEdit: Generalist Image Editing on Mobile Devices with Image-to-Image Diffusion Models

arXiv:2605.28067v1 Announce Type: new Abstract: The remarkable generation quality of modern diffusion models often comes at the cost of massive parameter counts, which necessitate server-side inferenc

Bounded-Compute Multimodal Regression for Product-Rating Prediction

arXiv:2605.27737v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly attractive for multimodal quality assessment, but their default reliance on autoregressive text generatio

BREAKING: Anthropic just dropped Opus 4.8—and it is a MONSTER We've been testing for about a week @every and our verdict is they could've ju…

BREAKING: Anthropic just dropped Opus 4.8—and it is a MONSTER We've been testing for about a week @every and our verdict is they could've just called it Opus 5, it's that good. Here's our vibe check:

model-releasesthariq--x

Bridging the Stability-Expressivity Gap: Synthetic Data Scaling and Preference Alignment for Low-Resource Spoken Language Models

arXiv:2605.27383v1 Announce Type: cross Abstract: Spoken Language Models (SLMs) have emerged as a promising paradigm for speech synthesis by bypassing explicit grapheme-to-phoneme pipelines. However,

BuddyBench: A Privacy-Constrained Multi-Task Benchmark for Pediatric Social-Communication Personalization

arXiv:2605.28089v1 Announce Type: new Abstract: BuddyBench introduces a privacy-constrained multi-task benchmark for pediatric social-communication personalization. Unlike existing neurodevelopmental

Build a test suite that grows with your agent with dataset management in Amazon Bedrock AgentCore

model-releasesaws-ml-blog

Agent evaluation is most powerful when you combine fast-moving online signals with stable offline baselines. To understand whether your agent is truly improving over time, you need a fixed benchmark a

Building Community-Centred NLP Resources for Puno Quechua

arXiv:2605.28253v1 Announce Type: new Abstract: The preservation of under-resourced languages requires digital tools and resources shaped by and for their speakers. We present the first dedicated ASR

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages

arXiv:2510.05291v2 Announce Type: replace Abstract: As Large Language Models (LLMs) develop stronger multilingual capabilities, their sensitivity to culturally diverse entities becomes increasingly im

Can Decision Trees Teach Large Language Models? Distilling Verbalized Knowledge for Molecular Property Prediction

arXiv:2603.12344v2 Announce Type: replace Abstract: Molecular Property Prediction (MPP) is a fundamental problem in drug discovery that has recently attracted growing attention. Large Language Models

Can Large Language Models Handle Discourse Particles? A Case Study of Colloquial Malay

arXiv:2605.28782v1 Announce Type: new Abstract: Discourse particles, such as extit{well} and extit{kind of}, are crucial components that enable LLMs to ``speak'' more like humans. They are used to con

Can Segmentation Models Understand the World? Towards Proactive Affordance Reasoning via Visual Chain-of-Thought

arXiv:2605.27764v1 Announce Type: cross Abstract: Recent segmentation models couple large language models (LLMs) with mask decoders to ground complex language expressions into masks, yet their instruc

CAREF: Calibration-Aware Regularization for Explanation Faithfulness Without Rationale Supervision

arXiv:2605.27835v1 Announce Type: cross Abstract: We introduce CAREF, a parameter-efficient fine-tuning framework that jointly optimizes predictive accuracy and explanation faithfulness via calibratio

Category-Level 3D Correspondence in Camera Space via Morphable Object Priors

arXiv:2605.28257v1 Announce Type: new Abstract: Understanding 3D objects from images is fundamental to robotics and AR/VR applications. While recent work has made progress in category-level pose estim

CFDTwin: An open-source GUI and Python toolkit for POD-NN surrogate modeling of ANSYS Fluent simulations

arXiv:2605.27725v1 Announce Type: cross Abstract: High-fidelity computational fluid dynamics (CFD) is widely used for thermal-fluid design, but repeated CFD solves remain expensive for design optimiza

ChildEval: When large language models meet children's personalities

arXiv:2605.27805v1 Announce Type: cross Abstract: While LLMs enable personalized chatbots, their effectiveness in child-centered personalization remains unclear, as systematic evaluation of child-spec

Chinese Word Boundary Recovery through Character Alignment Projection

arXiv:2605.28128v1 Announce Type: new Abstract: Chinese word segmentation is especially fragile in non-standard text, where language learner errors and other character-level divergences disrupt the wo