Search: “llm”

KVCapsule: Efficient Sequential KV Cache Compression for Vision-Language Models with Asymmetric Redundancy

arXiv:2605.16439v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have emerged as a critical and fast-growing extension of Large Language Models (LLMs) that enable multimodal reasoning t

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Lambda’s NVIDIA HGX 8xB200 on STAC-AI™ LANG6

DGX agent

What the numbers mean for financial services Executive summary Lambda is the first to publish an audited STAC-AI™ LANG6 result on NVIDIA HGX 8xB200, with independently verified performance data that F

model-releaseslambda-labs

19 May 2026

Latent Heuristic Search: Continuous Optimization for Automated Algorithm Design

arXiv:2605.17137v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into evolutionary frameworks has established a new paradigm for automated heuristic discovery. Despite t

researcharxiv-cs-ai

Learning Faster with Better Tokens: Parameter-Efficient Vocabulary Adaptation for Specialized Text Summarization

arXiv:2605.17379v1 Announce Type: cross Abstract: Large language models pretrained on general-domain corpora often exhibit tokenization inefficiencies when applied to specialized domains. Although con

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters

arXiv:2605.12012v2 Announce Type: replace Abstract: Public-sector legal departments in the Netherlands face acute staff shortages, increased case volumes, and increased pressure to meet regulatory com

Machine Unlearning for Masked Diffusion Language Models

arXiv:2605.18253v1 Announce Type: cross Abstract: Recent masked diffusion language models (MDLMs), such as LLaDA and Dream, have achieved performance comparable to autoregressive large language models

MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop

arXiv:2605.17159v1 Announce Type: new Abstract: Document processing automation remains a critical challenge in enterprise environments, where traditional manual approaches are labor-intensive and erro

MANTA: Multi-turn Assessment for Nonhuman Thinking & Alignment

arXiv:2605.16301v1 Announce Type: cross Abstract: Single-turn benchmarks such as AnimalHarmBench (AHB) have established important baselines for measuring animal welfare alignment in large language mod

MCQ Difficulty Prediction via Modeling Learner Heterogeneity Using Data-Driven Cognitive Profiling

arXiv:2605.16290v1 Announce Type: cross Abstract: Predicting the difficulty of multiple-choice questions (MCQs) is important for effective assessment, yet current methods typically assume a unimodal s

Med-V1: Small Language Models for Zero-shot and Scalable Biomedical Evidence Attribution

arXiv:2603.05308v2 Announce Type: replace-cross Abstract: Assessing whether an article supports an assertion is essential for hallucination detection and claim verification. While large language model

MemRepair: Hierarchical Memory for Agentic Repository-Level Vulnerability Repair

arXiv:2605.17444v1 Announce Type: cross Abstract: Modern software ecosystems face a rapidly growing number of disclosed vulnerabilities, increasing the need for automated repair techniques that can op

MirrorBench: A Benchmark to Evaluate Conversational User-Proxy Agents for Human-Likeness

arXiv:2601.08118v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as human simulators, both for evaluating conversational systems and for generating fine-tuning da

NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning

arXiv:2605.16757v1 Announce Type: new Abstract: Multi-agent language systems are often built as hand-designed workflows, where agents are assigned semantic roles and communication protocols are specif

NewsLens: A Multi-Agent Framework for Adversarial News Bias Navigation

model-releasesarxiv-cs-cl

arXiv:2605.17364v1 Announce Type: new Abstract: Media bias detection has predominantly been framed as a classification task: assign a political label to an article or outlet. We argue this framing is

NOETHER: A Constructive Framework for Metamorphic Pattern Discovery from Operator Algebras

arXiv:2605.17390v1 Announce Type: cross Abstract: Context. Metamorphic Testing is recognised in IEEE/ISO software-testing standards and increasingly recommended for AI systems, but its progress is bot

researcharxiv-cs-lg

Local Ai

NORM-Nav: Zero-Shot Mobile Robot Navigation with Natural Language Behavioral Constraints

arXiv:2605.16979v1 Announce Type: new Abstract: Mobile robots operating in human-centered environments must generate not only collision-free paths but also trajectories that follow local behavioral co

local-aiarxiv-cs-ro

Omni-DuplexEval: Evaluating Real-time Duplex Omni-modal Interaction

model-releasesarxiv-cs-cv

arXiv:2605.17360v1 Announce Type: new Abstract: Real-time duplex interaction is essential for multimodal AI systems operating in real-world scenarios, where models must continuously process streaming

PaliBench: A Multi-Reference Blueprint for Classical Language Translation Benchmarks

model-releasesarxiv-cs-cl

arXiv:2605.16881v1 Announce Type: new Abstract: Digital humanities projects increasingly rely on machine translation and large language models to widen access to classical, religious, and otherwise un

Peak-Detector: Explainable Peak Detection via Instruction-Tuned Large Language Models in Physiological Sign

arXiv:2605.16452v1 Announce Type: cross Abstract: Accurate peak detection across diverse cardiac physiological signals, including the Electrocardiogram (ECG), Photoplethysmogram (PPG), Ballistocardiog

Applications

Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design

arXiv:2507.16307v2 Announce Type: replace-cross Abstract: Perovskite solar cells (PSCs) have rapidly emerged as a leading contender in next-generation photovoltaic technologies, owing to their excepti

applicationsarxiv-cs-ai

ProfBench: Multi-Domain Rubrics requiring Professional Knowledge to Answer and Judge

arXiv:2510.18941v2 Announce Type: replace-cross Abstract: Evaluating progress in large language models (LLMs) is often constrained by the challenge of verifying responses, limiting assessments to task

PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship

arXiv:2605.17679v1 Announce Type: cross Abstract: Cancer survivors face elevated rates of depression, anxiety, and general emotional distress, yet the precise moments they most need support are often

QQJ: Quantifying Qualitative Judgment for Scalable and Human-Aligned Evaluation of Generative AI

arXiv:2605.17382v1 Announce Type: new Abstract: The rapid progress of generative artificial intelligence has exposed fundamental limitations in existing evaluation methodologies, particularly for open

Local Ai

RAPT: Retrieval-Augmented Post-hoc Thresholding for Multi-Label Classification

arXiv:2605.16535v1 Announce Type: cross Abstract: Industrial multi-label document understanding pipelines score candidate labels and threshold or rank them to form a label set per document. This early

local-aiarxiv-cs-ai

Real-Time Aligned Reward Model beyond Semantics

arXiv:2601.22664v4 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback (RLHF) is a pivotal technique for aligning large language models (LLMs) with human preferences, yet it is

Applications

Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift

arXiv:2605.16411v1 Announce Type: cross Abstract: Hallucination remains a fundamental challenge in vision-language models (VLMs), where autoregressive generation may produce linguistically plausible y

applicationsarxiv-cs-ai

Reliability and Effectiveness of Autonomous AI Agents in Supply Chain Management

arXiv:2605.17036v1 Announce Type: new Abstract: This paper studies autonomous generative AI agents in multi-echelon supply chains using the MIT Beer Game. We identify four inference-time levers that s

Reversa: A Reverse Documentation Engineering Framework for Converting Legacy Software into Operational Specifications for AI Agents

arXiv:2605.18684v1 Announce Type: cross Abstract: Legacy systems concentrate business rules, architectural decisions, and operational exceptions that often remain implicit in code, data, configuration

RLBFF: Binary Flexible Feedback to bridge between Human Feedback & Verifiable Rewards

arXiv:2509.21319v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Human Feedback (RLHF) and Reinforcement Learning with Verifiable Rewards (RLVR) are the main RL paradigms used in

Scales++: Compute Efficient Evaluation Subset Selection with Cognitive Scales Embeddings

arXiv:2510.26384v2 Announce Type: replace Abstract: The prohibitive cost of evaluating large language models (LLMs) on comprehensive benchmarks necessitates the creation of small yet representative da

SEMA-RAG: A Self-Evolving Multi-Agent Retrieval-Augmented Generation Framework for Medical Reasoning

arXiv:2605.17101v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is widely employed to mitigate risks such as hallucinations and knowledge obsolescence in medical question answer

Some[Body] Must Receive That Pain for Agent Accountability

arXiv:2605.16872v1 Announce Type: cross Abstract: AI agents increasingly act consequentially in the real world. This creates a problem we call consequence reception: harm occurs, the producing system

SPATIOROUTE: Dynamic Prompt Routing for Zero-Shot Spatial Reasoning

arXiv:2605.18209v1 Announce Type: cross Abstract: Spatial question answering over egocentric video is a challenging task that requires Vision-Language Models (VLMs) to reason about 3D object positions

StyleText: A Large-Scale Dataset and Benchmark for Stylized Scene Text Inpainting

arXiv:2605.17309v1 Announce Type: cross Abstract: We present StyleText, a large-scale dataset and benchmark for localized scene-text inpainting with style preservation. StyleText contains 28,518 image

Task Abstention for Large Language Models in Code Generation

arXiv:2605.17029v1 Announce Type: cross Abstract: Large language models (LLMs) have revolutionized automated code generation. One serious concern, however, is the so-called ``hallucination'', i.e., LL

Hardware

TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval

arXiv:2502.20969v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external data sources to enhance factual correctness and domain

hardwarearxiv-cs-lg

The future of agentic development: Redefining the data practitioner lifecycle with Data Agent Kit

model-releasesgoogle-cloud-ai

The modern software development landscape isn’t happening just on one surface — it’s happening across an entire ecosystem of agentic tools. Agents are being developed at an unprecedented scale, and th

The Lattice Representation Hypothesis of Large Language Models

arXiv:2603.01227v2 Announce Type: replace Abstract: We propose the Lattice Representation Hypothesis of large language models: a symbolic backbone that grounds conceptual hierarchies and logical opera

researcharxiv-cs-ai

Local Ai

TRACE: Evidence Grounding-Guided Multi-Video Event Understanding and Claim Generation

arXiv:2605.16740v1 Announce Type: new Abstract: Multi-video event understanding demands models that can locate and attribute query-relevant evidence scattered across long, heterogeneous video corpora.

local-aiarxiv-cs-cv

TRACE: Trajectory Correction from Cross-layer Evidence for Hallucination Reduction

arXiv:2605.18163v1 Announce Type: new Abstract: Hallucination correction is not a one-direction problem. We show that intermediate layers are neither uniformly more truthful than final layers nor unif

researcharxiv-cs-ai

Trustworthiness in Retrieval-Augmented Generation Systems: A Survey

arXiv:2409.10102v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has quickly grown into a pivotal paradigm in the development of Large Language Models (LLMs). Although ex

TTE-Flash: Accelerating Reasoning-based Multimodal Representations via Think-Then-Embed Tokens

arXiv:2605.16638v1 Announce Type: new Abstract: Recent research has demonstrated that Universal Multimodal Embedding (UME) benefits significantly from Chain-of-Thought (CoT) reasoning. In this paradig

TusoAI: Agentic Optimization for Scientific Methods

arXiv:2509.23986v2 Announce Type: replace Abstract: Scientific discovery is often slowed by the manual development of computational tools needed to analyze complex experimental data. Building such too

Vidya: An AI-Driven Modular Pipeline for Archival Automation and Semantic Metadata Enrichment

arXiv:2605.16338v1 Announce Type: cross Abstract: The large-scale digitization of historical archives has created a paradox: 'dark data'-digital objects lacking metadata for retrieval. Manual archival

researcharxiv-cs-cl

VLM-AutoDrive: Post-Training Vision-Language Models for Safety-Critical Autonomous Driving Events

arXiv:2603.18178v2 Announce Type: replace-cross Abstract: The rapid growth of ego-centric dashcam footage presents a major challenge for detecting safety-critical events such as collisions and near-co

What Does the AI Doctor Value? Auditing Pluralism in the Clinical Ethics of Language Models

arXiv:2605.18738v1 Announce Type: new Abstract: Medicine is inherently pluralistic. Principles such as autonomy, beneficence, nonmaleficence, and justice routinely conflict, and such ethical dilemmas

What Google I/O '26 means for developing agents on Google Cloud

model-releasesgoogle-cloud-ai

At Google I/O, we introduced a unified development toolkit featuring Antigravity 2.0 and the Managed Agents API, giving developers better ways to build locally and deploy securely to the cloud on a sh

When AI Tells You What You Want to Hear: Sycophantic Behavior of Large Language Models in Dementia Care Settings

model-releasesarxiv-cs-cl

arXiv:2605.16288v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in clinical and care settings. This exploratory study investigates whether LLMs exhibit sycophantic