Search: “llm”

VIB-AVSR: Variational Information Bottleneck for Noise-Robust LLM-Based Audio-Visual Speech Recognition

arXiv:2606.29632v1 Announce Type: cross Abstract: Audio-Visual Speech Recognition takes two input modalities, acoustic and visual streams, where visual information from lip movements aids recognition

researcharxiv-cs-cv

30 Jun 2026

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Model Releases

When Does Overlap Help? OSU-Mem and a Cell-Conditional Analysis of Trajectory Memory for LLM Agents

DGX agent

arXiv:2606.28376v1 Announce Type: cross Abstract: Long-horizon large language model (LLM) agents accumulate interaction trajectories that quickly exceed any practical prompt budget, and existing memor

model-releasesarxiv-cs-ai

30 Jun 2026

Check Yourself Before You Wreck Yourself: Selectively Quitting Improves LLM Agent Safety

arXiv:2510.16492v4 Announce Type: replace Abstract: As Large Language Model (LLM) agents increasingly operate in complex environments with real-world consequences, their safety becomes critical. While

safetyarxiv-cs-cl

Hierarchical Control in Multi-Agent Games: LLM-based Planning and RL Execution

arXiv:2606.20014v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has achieved strong performance in sequential decision-making, yet scaling to complex multi-agent environments rem

Tutorials

LLM-as-a-Judge explained in ~10 mins. Knowing how to build AI verifiers and judges is one of the most important emerging AI skills today. He…

LLM-as-a-Judge explained in ~10 mins. Knowing how to build AI verifiers and judges is one of the most important emerging AI skills today. Here is a quick intro on the topic and where to learn how to a

tutorialsdair-ai--x

Multi-tenant LLM analytics with row-level security: How we built a secure agent on AWS

In this post, we show you how PAR built a production-ready multi-tenant LLM analytics system that enforces row-level security through a three-layer architecture: cryptographic request signing with AWS

agentsaws-ml-blog

Yuvion LLM: An Adversarially-Aware Large Language Model for Content And AI Safety

arXiv:2606.27632v1 Announce Type: new Abstract: As large language models are increasingly deployed in real-world systems, safety failures can still lead to harmful outputs and dangerous misuse. We arg

Semantic Early-Stopping for Iterative LLM Agent Loops

arXiv:2606.27009v1 Announce Type: new Abstract: Multi-agent large language model (LLM) loops, for example a Writer that drafts and a Critic that revises, are almost always terminated by a fixed iterat

26 Jun 2026

Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods

arXiv:2606.26130v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to guide research methodology, yet their default methodological tendencies under minimal prompting

26 Jun 2026

Am I More Pointwise or Pairwise? Revealing Position Bias in Rubric-Based LLM-as-a-Judge

arXiv:2602.02219v2 Announce Type: replace Abstract: Large language models are widely employed as evaluators, a paradigm commonly referred to as LLM-as-a-judge. Prior research has predominantly examine

safetyarxiv-cs-cl

25 Jun 2026

CARE: Controlling LLM-Generated Policies through Auditable Review of Evidence in Scientific Experimentation

arXiv:2606.14581v2 Announce Type: replace Abstract: Granting LLMs direct control over costly, irreversible scientific experiments leads to unsafe exploration and unstable performance, but discarding L

researcharxiv-cs-lg

25 Jun 2026

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction

arXiv:2606.24420v1 Announce Type: new Abstract: In high-stakes document processing pipelines, including financial reconciliation, compliance verification, and procurement automation, an LLM extraction

CompressKV: Semantic-Retrieval-Guided KV-Cache Compression for Resource-Efficient Long-Context LLM Inference

arXiv:2606.24467v1 Announce Type: new Abstract: Long-context large language model (LLM) inference is increasingly constrained by the memory footprint and decoding cost of key-value (KV) caches, limiti

CORE-BREW: LLR-Based Soft Decoding for Robust Multi-Bit LLM Watermarking

arXiv:2606.24163v1 Announce Type: cross Abstract: Reliable provenance for LLM outputs requires multi-bit watermarks that remain robust under editing while maintaining strict false-positive control. Ex

Local Ai

CrossPool: Efficient Multi-LLM Serving for Cold MoE Models through KV-Cache and Weight Disaggregation

arXiv:2606.24506v1 Announce Type: cross Abstract: Emerging LLM services increasingly host many sparse MoE models, yet most models receive sparse requests and remain cold. This creates a GPU memory pro

local-aiarxiv-cs-ai

Do LLM Attribution Metrics Transfer? Auditing Retrieval-Augmented Generation Evaluation Across Datasets and Constructs

arXiv:2606.23915v1 Announce Type: new Abstract: Practice often treats automatic metrics for attribution in LLM retrieval-augmented generation as interchangeable. We audit eight automatic scorers -- le

Holistic Data Scheduler for LLM Pre-training via Multi-Objective Reinforcement Learning

arXiv:2606.24133v1 Announce Type: cross Abstract: The composition of training data, governed by the diversity of sources and their mixing strategy, is a cornerstone of Large Language Model (LLM) pre-t

Policies Permitting LLM Use for Polishing Peer Reviews Are Currently Not Enforceable

arXiv:2603.20450v2 Announce Type: replace-cross Abstract: A number of scientific conferences and journals have recently enacted policies that prohibit LLM usage by peer reviewers, except for polishing

SciZoom: A Large-scale Benchmark for Hierarchical Scientific Summarization across the LLM Era

arXiv:2603.16131v2 Announce Type: replace Abstract: The explosive growth of AI research has created unprecedented information overload, increasing the demand for scientific summarization at multiple l

Distribution-Aware Diffusion-LLM for Robust Ultra-Long-Term Time Series Forecasting

arXiv:2606.23391v1 Announce Type: new Abstract: Time series forecasting is a fundamental machine learning task. Recent work has explored Large Language Models (LLMs) for this purpose due to their stro

safetyarxiv-cs-lg

FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation

arXiv:2606.23370v1 Announce Type: cross Abstract: Device-side Large Language Models (LLMs) have grown explosively, offering stronger privacy and higher availability than their cloud-side counterparts.

researcharxiv-cs-lg

GRADE: Graph Representation of LLM Agent Dependency and Execution

arXiv:2606.22741v1 Announce Type: new Abstract: Can one graph represent every kind of LLM agent's run? A trace records what each step did, never what it relied on, the state it read, and the results i

agentsarxiv-cs-lg

ReNIO: Reweighting Negative Trajectory Importance for LLM On-Policy Distillation

model-releasesarxiv-cs-lg

arXiv:2606.23104v1 Announce Type: new Abstract: On-policy distillation (OPD) improves LLM reasoning by training a student model on its own generated outputs, but standard OPD treats all student-genera

Specialize Roles, Mix Deployments: Pushing the Cost-Accuracy Frontier of LLM Agent Teams

model-releasesarxiv-cs-lg

arXiv:2606.20629v1 Announce Type: cross Abstract: LLM agents are increasingly deployed as multi-role teams, where tasks are divided across specialized roles such as planner, executor, and verifier. In

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications

model-releasesarxiv-cs-lg

arXiv:2512.08211v2 Announce Type: replace Abstract: Large language models (LLMs) are moving from cloud-centric services toward on-device embedded AI, where models interact with private, longitudinal s

11 Jun 2026

SPEAR: A System for Post-Quantization Error-Adaptive Recovery Enabling Efficient Low-Bit LLM Serving

arXiv:2606.11244v1 Announce Type: cross Abstract: Efficient large language model (LLM) serving is increasingly constrained by deployment cost. Quantization is a key technique for reducing serving cost

11 Jun 2026

Applications

T2MM: An LLM Supported Architecture For Inquiry-Based Modeling

arXiv:2606.11210v1 Announce Type: cross Abstract: Model Construction is a foundational practice in science learning that relies on visualization and interactivity. Large Language Models, increasingly

applicationsarxiv-cs-ai

11 Jun 2026

BadRobot: Jailbreaking Embodied LLM Agents in the Physical World

arXiv:2407.20242v5 Announce Type: replace-cross Abstract: Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language und

Beyond Static Evaluation: Co-Evolutionary Mechanisms for LLM-Driven Strategy Evolution in Adversarial Games

arXiv:2606.10389v1 Announce Type: new Abstract: Recent advances in LLM-driven code evolution have enabled automated discovery by iteratively generating and improving programs. However, applying these

Catching One in Five: LLM-as-Judge Blind Spots in Production Multi-Turn Transaction Agents

arXiv:2606.10315v1 Announce Type: cross Abstract: LLM-as-judge is the default instrument for evaluating conversational agents, yet its reliability is almost always reported as agreement with human rat

Emotion Profiling in LLM-Based Literary Translation: Systematic Shifts Across MT and Post-Editing

arXiv:2606.10113v1 Announce Type: cross Abstract: This paper investigates whether LLM translations exhibit identifiable emotional profiles and how post-editing reshapes them toward human-like norms. W

From Perception to Action: Can UI Interventions Foster Sustainable LLM Chatbot

arXiv:2606.10861v1 Announce Type: cross Abstract: LLM-powered chatbots are increasingly embedded in everyday workflows, raising sustainability concerns due to their energy use. Most mitigation strateg

Infini Memory: Maintainable Topic Documents for Long-Term LLM Agent Memory

arXiv:2606.10677v1 Announce Type: new Abstract: Long-term LLM agents need persistent memory that can track changing facts and provide relevant evidence across sessions. Existing memory systems often s

shoutouts: • why multi-agent LLM systems fail? (arXiv:2503.13657) — @mertcemri @melissapan + @istoica05 @matei_zaharia @profjoeyg @adityagp …

shoutouts: • why multi-agent LLM systems fail? (arXiv:2503.13657) — @mertcemri @melissapan + @istoica05 @matei_zaharia @profjoeyg @adityagp & team • DSPy (arXiv:2310.03714) — @lateinteraction + @hazyr

agentsyohei-nakajima--x

Sim2Schedule: A Simulator-Guided LLM Framework for Autonomous Open-Pit Mine Scheduling

arXiv:2606.10286v1 Announce Type: new Abstract: Open-pit mine scheduling is a critical process for maximizing economic return under complex geotechnical and operational constraints. While Mixed-Intege

Streaming Knowledge Compilation: Proactive Materiality-Scored Pinning for Time-Evolving LLM Wikis

arXiv:2606.09877v1 Announce Type: cross Abstract: LLM wiki systems compile knowledge into pre-filled KV caches for efficient inference, but assume a static corpus -- an assumption that fails whenever

Who Wrote the Book? Detecting and Attributing LLM Ghostwriters

arXiv:2603.28054v2 Announce Type: replace Abstract: In this paper, we introduce GhostWriteBench, a dataset for LLM authorship attribution. It comprises long-form texts (50K+ words per book) generated

Agentic Search for Counterfactual Recourse under Fixed LLM Budgets

arXiv:2606.08696v1 Announce Type: cross Abstract: Counterfactual recourse aims to provide actionable feature changes that would alter an unfavorable decision made by a predictive model. In practice, a

Beyond FLOPs: Benchmarking Real Inference Acceleration of LLM Pruning under a GEMM-Centric Taxonomy

arXiv:2606.09080v1 Announce Type: new Abstract: Pruning has emerged as a dominant paradigm for accelerating large language model (LLM) inference, spanning a broad spectrum of methods that remove compu

researcharxiv-cs-lg

Byzantine Cheap Talk: Adversarial Resilience and Topology Effects in LLM Coordination Games

arXiv:2606.07790v1 Announce Type: new Abstract: Multi-agent LLM systems increasingly rely on communication protocols for coordination, yet their robustness under adversarial and structural constraints

agentsarxiv-cs-lg

Causal Agent Replay: Counterfactual Attribution for LLM-Agent Failures

arXiv:2606.08275v1 Announce Type: cross Abstract: When an LLM agent fails -- issues a refund it should not have, calls the wrong tool, leaks data -- existing tooling answers what happened (observabili

Context-Fractured Decomposition Attacks on Tool-Using LLM Agents: Exploiting Artifact Provenance Gaps

arXiv:2606.09084v1 Announce Type: cross Abstract: Tool-using LLM agents interact with the world through actions that persist state in artifacts (e.g., workspace files or logs). Consequently, jailbreak

REFLECT: Intervention-Supported Error Attribution for Silent Failures in LLM Agent Traces

arXiv:2606.09071v1 Announce Type: new Abstract: Large language model (LLM) agents now solve complex tasks through long plan-and-execution traces, yet the ability to locate errors in a completed traces

Rethinking the Divergence Regularization in LLM RL

arXiv:2606.09821v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a key component of post-training large language models (LLMs). In practice, LLM RL is often off-policy because of

safetyarxiv-cs-lg

Safety is Contextual, LLM-Judges Are Not: Navigating the Rigid Priors of Evaluators

arXiv:2606.07874v1 Announce Type: new Abstract: LLMs-as-judges are the only way to evaluate safety at scale. Despite their importance, LLM-judges themselves are rarely evaluated beyond human agreement

'So There's a Catch-22 Here': How Early Adopters Who Build Multi-Agent LLM Systems Conceptualize Transparency

arXiv:2606.08323v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems are rapidly emerging, yet transparency, a cornerstone of responsible AI, remains under-defined in these

When Does Delegation Beat Majority? A Delegation-Based Aggregator for Multi-Sample LLM Inference

arXiv:2606.08098v1 Announce Type: new Abstract: Majority voting over sampled answers is the dominant unsupervised aggregator for multi-sample LLM inference. We show that piping the signals every sampl

Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates

arXiv:2601.18510v2 Announce Type: replace-cross Abstract: While Large Language Model (LLM) agents excel at general tasks, they inherently struggle with continual adaptation due to the frozen weights a