Search: “llm”

arXiv:2609.07843v1 Announce Type: cross Abstract: Machine learning has shown its largest gains in the band below 10 ms inside a 3GPP new radio (NR) 5G distributed unit (DU): link adaptation, per-slot

hardwarearxiv-cs-lg

9 Sept 2026

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TontaubeV1: Streaming Text-to-Speech with Hierarchical Codec Modeling and Bounded Context

DGX agent

arXiv:2609.08703v1 Announce Type: cross Abstract: Text-to-speech systems often face a trade-off between natural prosody and efficient inference: higher perceptual quality typically comes at increased

model-releasesarxiv-cs-lg

9 Sept 2026

When and What to Teach: Budget-Aware Online Adaptation for Web Agents

arXiv:2609.05513v1 Announce Type: cross Abstract: Web agents have achieved significant success in automating complex internet tasks but deploying them in real-world environments requires continuous on

local-aiarxiv-cs-cv

9 Sept 2026

When Retain Constraints Conflict: Mitigating Forget-Retain Interference in Tabular Data

arXiv:2609.06786v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of designated training data while preserving model utility, but its behavior on tabular data remains und

researcharxiv-cs-lg

9 Sept 2026

AlcaTRAz - Anchored Tree-Rule Defense Against Jailbreaks

arXiv:2609.03693v1 Announce Type: cross Abstract: Large language models (LLMs) are vulnerable to jailbreak attacks that bypass safety alignment through carefully crafted prompts. Many existing defense

AutoLR: Automating the Path from Research to Launch Review in Industrial Recommender Systems

arXiv:2609.04871v1 Announce Type: new Abstract: Improving an industrial recommender is an iterative research-and-engineering process rather than a direct path from idea to deployment. In extbf{DASHEN,

Beyond Aggregate Scores: Behavioral Correctness Assumptions for Assessing Reference-Based Automatic Evaluation Methods

arXiv:2609.05289v1 Announce Type: new Abstract: Automated reference-based evaluation methods play a critical role in assessing natural language generation systems. Existing meta-evaluation primarily m

Applications

Beyond Co-purchase Relation: Evolution of Complementary Recommendations at Allegro

arXiv:2609.05063v1 Announce Type: cross Abstract: When a customer adds a professional camera to their cart, should the system suggest a matching lens, a generic tripod, or another camera body? Complem

applicationsarxiv-cs-ai

Hardware

BIT.UA at BioASQ 14B: Modular Retrieval with pg_textsearch and Qdrant, and Agent-Based Answer Generation

arXiv:2609.04999v1 Announce Type: new Abstract: This paper describes the participation of the BIT.UA team from the University of Aveiro in the 14th edition of the BioASQ Task B challenge on biomedical

hardwarearxiv-cs-cl

CABAL: Multi-Agent Simulacra for Tracing the Effects of Collusive Bidding in Peer Review

arXiv:2609.05227v1 Announce Type: new Abstract: Recent reports during the AAAI-27 review cycle highlight the risk of reviewers coordinating bids for reciprocal assignment advantage. Prior work treats

Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution

arXiv:2609.04820v1 Announce Type: cross Abstract: Ransomware detection and family attribution require analysis of different modalities because it can use packing, obfuscation, process manipulation and

local-aiarxiv-cs-ai

Cross-Task Generalization Between Understanding and Generation in Unified Vision-Language Models: A Controlled Study

arXiv:2505.23043v2 Announce Type: replace-cross Abstract: Unified vision-language models (VLMs) aim to support both visual understanding and generation within a single framework, but it remains unclea

researcharxiv-cs-ai

Development of a Humanoid Robot Prototype for Multimodal Human-Robot Interaction

arXiv:2609.05361v1 Announce Type: new Abstract: Human-robot interaction (HRI) enables intuitive and intelligent collaboration between humans and robots in real-world environments. This paper introduce

local-aiarxiv-cs-ro

Evaluating Large Language Models for Forced Outage Risk Prediction: Benefits and Comparison to Machine Learning

arXiv:2609.04272v1 Announce Type: cross Abstract: This study examines the ability of large language models (LLMs) to predict the risk of weather-related forced outages in the distribution grid in a ze

researcharxiv-cs-cl

Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving

arXiv:2509.22480v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been widely used for problem-solving tasks. Most recent work improves their performance through supervised f

researcharxiv-cs-ai

From Matching Models to Recruiting Agents: A Systematized Narrative Review of AI Recruitment Systems, Evaluation, and Governance

arXiv:2609.04286v1 Announce Type: new Abstract: Artificial intelligence in recruitment has shifted the object being automated from profile pairs and ranked lists to multi-stage workflows that retrieve

safetyarxiv-cs-ai

Generating Constructive Feedback on Stories via Reinforcement Learning

arXiv:2609.04824v1 Announce Type: new Abstract: Constructive feedback is crucial for creative writers to refine their storytelling abilities. Since receiving feedback from human experts is often costl

GLOW: Graph-Language Co-Encoding for Agentic Workflow Performance Prediction

arXiv:2512.15751v2 Announce Type: replace-cross Abstract: Agentic Workflows (AWs) have emerged as a promising paradigm for solving complex tasks. However, automatically generating high-quality AWs rem

Hakken: Predicting future discoveries to fill the gaps in today's knowledge

arXiv:2609.04494v1 Announce Type: cross Abstract: We present Hakken, a domain-agnostic prediction and explanation system performing knowledge prediction, i.e., growing scientific knowledge by establis

MABPD: Multi-Agent Bias Probing & Detection via Structured Argument Debate

arXiv:2609.04841v1 Announce Type: cross Abstract: Media bias in news articles operates through subtle linguistic cues---loaded language, selective framing, and strategic omission---that resist single-

MaxKernel: Agentic Kernel Generation for TPUs

arXiv:2609.04523v1 Announce Type: new Abstract: Designing and authoring high-performance custom kernels for accelerators is a complex task that requires deep hardware-level expertise. Large Language M

Model Retirement Creates Reproducibility Risk in Biomedical AI Publications

arXiv:2609.04699v1 Announce Type: new Abstract: Background. Large language models (LLMs) are being adopted in biomedical research at a rapid and accelerating pace, yet commercial services that host ma

Molecular Deja Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

arXiv:2609.05381v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated on molecular property benchmarks, but accuracy cannot distinguish a model that predicts a proper

Motion-Omni: End-to-End Joint Speech and Full-Body Motion for Spoken Dialogue

arXiv:2609.04250v1 Announce Type: cross Abstract: An avatar that holds a conversation should decide what to say and to move while saying it, yet these abilities live in separate model families: spoken

safetyarxiv-cs-cv

PetQA: Benchmarking Veterinary Knowledge and Clinical Reasoning

arXiv:2609.04598v1 Announce Type: cross Abstract: We introduce PetQA, a Korean long-form question-answering (QA) benchmark for evaluating veterinary knowledge and clinical reasoning in large language

PLUME: Parameter-Efficient Personalization of Large Language Models via Low-Rank User Modulation in Shared Subspaces

arXiv:2609.04715v1 Announce Type: new Abstract: Personalizing large language models (LLMs) is essential for delivering AI assistance that aligns with individual users' styles, intents, and preferences

QoNext: Towards Next-generation QoE for Foundation Models

arXiv:2509.21889v3 Announce Type: replace Abstract: Existing evaluations of foundation models predominantly focus on output correctness, treating interaction as a static exchange of information. Howev

researcharxiv-cs-cl

RL-VLA^3: A Flexible and Asynchronous Reinforcement Learning Framework for VLA Training

arXiv:2602.05765v3 Announce Type: replace Abstract: Reinforcement learning (RL) has emerged as a critical paradigm for post-training Vision-Language-Action (VLA) models, enabling embodied agents to ad

safetyarxiv-cs-ai

Single-Query Black-Box Calibration Auditing via Logit Bias

model-releasesarxiv-cs-lg

arXiv:2609.05125v1 Announce Type: new Abstract: Evaluating the calibration of Large Language Models (LLMs) is critical for their safe deployment as zero-shot classifiers. Yet, commercial API providers

SQL-Zero: Self-Evolving Text-to-SQL

arXiv:2609.04697v1 Announce Type: new Abstract: Training a competitive Text-to-SQL agent usually depends on human-annotated natural-language/SQL pairs, which are expensive, domain-specific, and a bott

TeleTables: A Benchmark for Large Language Models in Telecom Table Interpretation

arXiv:2601.04202v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly applied to telecom engineering tasks, yet perform poorly on 3GPP specifications. These standards

TROVE: Adaptive Agent Skill Orchestration via Trace-Grounded Route Validation and Editing

arXiv:2609.05019v1 Announce Type: new Abstract: Agents tend to optimize, select, or constrain execution structures before decisive runtime outcomes are observed. However, such pre-execution commitment

local-aiarxiv-cs-ai

TruthInsightBench: An Evidence-Grounded Benchmark for Automated Evaluation of Open-Ended Scientific Discovery Agents

arXiv:2609.05079v1 Announce Type: new Abstract: Autonomous coding agents are increasingly proposed as AI-scientist systems that conduct analyses and write research reports, but executing a prescribed

WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data

arXiv:2609.05405v1 Announce Type: new Abstract: Recent advances in wearable sensing enable continuous monitoring of physiological and behavioral signals, yet existing benchmarks rarely evaluate whethe

A location-invariant estimator of extremal quantile treatment effects for heavy-tailed distributions

model-releasesarxiv-cs-lg

arXiv:2609.04018v1 Announce Type: new Abstract: Quantile treatment effects (QTEs) measure the effect of a treatment on the distribution of an outcome, and their estimation at extreme quantile levels i

Benchmarking Machine Translation on Chinese Social Media Texts

arXiv:2601.22931v2 Announce Type: replace Abstract: The prevalence of rapidly evolving slang, neologisms, and highly stylized expressions in informal user-generated text, particularly on Chinese socia

Beyond Endpoint Scores: Time- and Capacity-Conditioned Evaluation of Continual Knowledge Updating

model-releasesarxiv-cs-lg

arXiv:2609.03900v1 Announce Type: new Abstract: Continual knowledge-updating methods are often declared superior from one final checkpoint and one conventional adapter rank. We show that this can be i

Beyond Majority Vote: Multi-Perspective Adjudication for Medical Hallucination Detection

arXiv:2609.03953v1 Announce Type: new Abstract: Understanding the frequency of factual errors in chatbot-generated text and evaluating systems that detect these errors is critical for determining chat

Beyond Reproducibility: Towards Security-Aware Evaluation of Research Artifacts

arXiv:2605.06508v2 Announce Type: replace-cross Abstract: Research artifacts are widely shared to support reproducibility, and artifact evaluation (AE) has become common at many leading conferences. H

Bounded Personas Match Retrieval on Classification but Not Regression for a Frozen Agent

arXiv:2609.02890v1 Announce Type: new Abstract: A personalized language agent must convert a user's interaction history into behavior on each new request at inference time. Two strategies dominate. Re

agentsarxiv-cs-cl

CauseCollab: Causal Unified and Modality-Agnostic Network for Heterogeneous Collaborative Perception

arXiv:2609.03818v1 Announce Type: new Abstract: Collaborative perception enhances environment understanding through multi-agent information sharing, but its performance in real-world scenarios is cons

Chiaroscuro for Emotions: A Contrastive Emotion Benchmark Grounded in Appraisal Theory

arXiv:2609.03394v1 Announce Type: new Abstract: Emotion recognition benchmarks often predict one emotion per text, missing many real-world scenarios where two people arrive at opposing emotions from a

CoFiE: Coarse-to-Fine Evidence Selection for Efficient Streaming Video Understanding

arXiv:2609.03675v1 Announce Type: new Abstract: Streaming video understanding requires Vision Language Models (VLLMs) to process growing video streams and answer user questions under tight latency con

researcharxiv-cs-cv

Counterexamples as Feedback for Agent Self-Correction

arXiv:2609.02892v1 Announce Type: cross Abstract: Single-turn code-generation metrics understate a central property of deployed agents: whether they can repair a wrong artifact after receiving concret

Dalek: A Constructive Agent Machine

arXiv:2609.03546v1 Announce Type: new Abstract: We present Dalek, a closed machine designed for agents that realizes self-maintenance, self-evolution, self-reproduction, and self-organization on any s

DE-Venus: A Data-Efficient RLVR Framework for Large Language Models

arXiv:2609.03324v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves large language model reasoning, but its practical scaling is constrained by expensive on-

safetyarxiv-cs-lg

Detecting Conversational Mental Manipulation with Intent-Aware Prompting

arXiv:2412.08414v2 Announce Type: replace Abstract: Mental manipulation severely undermines mental wellness by covertly and negatively distorting decision-making. While there is an increasing interest

researcharxiv-cs-cl

DRACO: Fine-Grained Credit Assignment with Dynamic Rubrics for Long-Horizon Agent Training

arXiv:2609.04094v1 Announce Type: new Abstract: Reinforcement Learning from Verifiable Rewards works well when a task has a programmatic checker, but most long-horizon agent domains have none. We work

safetyarxiv-cs-ai