Search: “llm”

TeleAntiFraud 2.0: A Refreshable, Profile-Grounded, and Audio-Based Benchmark for Telecom Fraud Detection

arXiv:2609.18748v1 Announce Type: cross Abstract: Telecom fraud scripts evolve rapidly and are often designed to resemble routine service conversations, creating two key requirements for audio-based t

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Research

Training-Adaptive Convolutional Sparse Coding via Information Bottleneck for Robust Visual Representation

DGX agent

arXiv:2609.19122v2 Announce Type: new Abstract: Visual signals require compact yet sufficient representations for robust downstream prediction. Convolutional sparse coding (CSC) provides an explicit m

researcharxiv-cs-cv

17 Sept 2026

Training Lora with 2x 5060 Ti

model-releasesr-stablediffusion

Another question asked 1 thousand time, but I can't find actual threads. Sorry in case of mistake. Due to interstellar price of hardware like high-end GPU (more than 5k euros for a 5090 and similar pr

TuiML: Machine Learning for AI Agents

arXiv:2609.17984v1 Announce Type: new Abstract: Machine-learning libraries such as Weka and scikit-learn were designed for human programmers. Language-model agents now use these same libraries by reca

Understanding AI Provider Recommendations in Local Service Markets

arXiv:2609.18341v1 Announce Type: cross Abstract: When someone asks an AI assistant which doctor to see or which firm to trust with their savings, the answer is a referral. We audit AI provider recomm

v0.34.2-rc2: mlxrunner: Release freed KV buffers during speculative decode

model-releasesollama-releases

The decode loop releases MLX's pool of freed buffers every 256 generated tokens, which is also how often the KV cache grows and drops its previous, smaller buffers. The check fires only when the token

Weakening Neurons: An Input-Output Functionality in Transformers with Outsize Influence

arXiv:2609.18612v1 Announce Type: cross Abstract: We analyze the learned input-output behavior of GLU-based neurons in large language models (LLMs). We propose a simple analysis method: For each neuro

Where Should Agents Live? Energy-Memory Characterization of Agentic AI for the Edge-Cloud Continuum

arXiv:2609.18283v1 Announce Type: new Abstract: As telecommunication networks evolve toward autonomous 5G-Advanced and 6G operations, agentic artificial intelligence (AI) workflows, where large langua

Who Audits Whom, on What Substrate, with What Evidence? An Independence-Graded Audit Protocol for Agentic AI

arXiv:2609.18272v1 Announce Type: new Abstract: Agentic AI systems plan, invoke tools and act with limited supervision; they are now both the subject of audits and, increasingly, the auditor. Independ

safetyarxiv-cs-ai

WordPolo: Evaluating Language Models Through Iterative Semantic Feedback

arXiv:2609.19006v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Large Reasoning Models (LRMs) are typically evaluated on challenging benchmarks through dataset accuracy alone, provi

Applications

Affect-Prototype Guided Fusion for Open-Vocabulary Incomplete Multi-modal Emotion Recognition

arXiv:2609.16962v1 Announce Type: new Abstract: Open-vocabulary multimodal emotion recognition (OV-MER) aims to generate open natural-language emotion labels from multimodal affective cues. In real-wo

applicationsarxiv-cs-ai

Autoformalizing Argumentative Material Inferences

arXiv:2609.16991v1 Announce Type: new Abstract: Natural language arguments are compelling before they are formally explicit. A premise supports a claim through defeasible warrants, background commitme

Hardware

Banger paper from NVIDIA. It's on the topic of choosing which models go into a multi-agent system. The team compared eight selection strateg…

Banger paper from NVIDIA. It's on the topic of choosing which models go into a multi-agent system. The team compared eight selection strategies, based on size, accuracy, answer diversity and error div

hardwaredair-ai--x

Tutorials

Beyond 'ChatGPT Can Make Mistakes': Designing Interventions to Support Metacognitive Monitoring in AI-Assisted Work

arXiv:2609.17065v1 Announce Type: cross Abstract: AI assistance places a metacognitive demand on users, who must judge their own competence and the system's. Yet designers lack comparative evidence on

tutorialsarxiv-cs-ai

Agents

CLEAR: Cross-Source Evidence Adjudication for Large Language Models in Medicine

arXiv:2609.16301v1 Announce Type: new Abstract: Medical knowledge evolves continuously, whereas the parametric knowledge encoded in large language models (LLMs) is fixed at training time. External ret

agentsarxiv-cs-ai

Cloud CISO Perspectives: How Google monitors AI threats and advances AI defenses

model-releasesgoogle-cloud-ai

Welcome to the first Cloud CISO Perspectives for September 2026. Today, Sandra Joyce shares the latest details on Google’s visibility into how attackers are using AI, and how we’re using AI to stop th

Crash Narrative-Guided Countermeasure Recommendation Using Large Language Models: A Retrieval-Augmented Generation Framework for Intersection Safety

arXiv:2609.15997v1 Announce Type: new Abstract: Improving safety at intersections requires identifying crash mechanisms and recommending appropriate countermeasures. However, this process traditionall

Enhancing Accessibility of Medical Texts through Large Language Model-Driven Plain Language Adaptation

arXiv:2609.17398v1 Announce Type: new Abstract: This paper addresses the challenge of making complex healthcare information more accessible through automated Plain Language Adaptation (PLA). PLA aims

Agents

Glyph: A Multi-Strategy Agentic System for Column Description and Sensitivity-Ontology Tagging of Enterprise Data Catalogs

Enterprise data lakes accumulate tables faster than human stewards can document or classify them, leaving columns with missing descriptions and unassigned governance labels. This documentation debt un

agentsapple-ml-research

GrowMTP: Can RL Grow Its Own Draft Head?

arXiv:2609.16648v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training drives the frontier capabilities of large language models, with its wall-clock dominated by autoregressive r

Applications

Large Language Models Develop Belief State Geometry In-Context

arXiv:2609.17376v1 Announce Type: cross Abstract: Large language models (LLMs) trained on next-token prediction exhibit remarkable in-context learning (ICL) abilities, yet the representations that sup

applicationsarxiv-cs-cl

little m: An AI Agent for Industrial Process Optimization

arXiv:2609.16680v1 Announce Type: new Abstract: Manufacturing consumes one third of global energy and still has significant room for improvement in terms of energy efficiency. Optimal process control

ManiSkillFormer: Demonstration-Free Compositional Manipulation via Task-Conditioned Geometric Contracts

arXiv:2609.16331v1 Announce Type: new Abstract: We present ManiSkillFormer, a neuro-symbolic framework for demonstration-free and compositional robotic manipulation. Instead of learning end-to-end vis

safetyarxiv-cs-ro

MUUNRiver-Bench: Diagnosing Relation-Dependent Music Retrieval with Multimodal Instructions

arXiv:2609.16090v1 Announce Type: cross Abstract: Music retrieval is relation-dependent: given a reference track, a listener may seek its style with a new theme, a cover, or a comparable voice, and th

Nice work from Adobe. It's standard practice to store a fixed reference answer for every eval case. When the underlying data changes daily, …

Nice work from Adobe. It's standard practice to store a fixed reference answer for every eval case. When the underlying data changes daily, that stored answer goes stale. Adobe researchers write each

model-releasesdair-ai--x

Nonsmooth Optimization via Orthogonalized Momentum

model-releasesarxiv-cs-lg

arXiv:2609.13677v1 Announce Type: cross Abstract: Modern real application problems involve matrix-valued parameters, yet conventional optimizers treat them as vectors, thereby motivating matrix-aware

Optimal Pruning for Neural Architectures using Fisher Information Distances

arXiv:2609.16129v1 Announce Type: new Abstract: A new scheme for parameter pruning is introduced, derived from the differential-geometric distance in model space. Pruning a parameter sets its value to

PunGraph: Retrieval-Enhanced Phonetic-Semantic Graph Reasoning for Pun Understanding

arXiv:2609.16557v1 Announce Type: new Abstract: Puns are a challenging form of figurative language that exploit phonetic similarity and semantic ambiguity to convey multiple meanings. Although large l

StalePO: Anchored Token-Level Preference Optimization using Legacy Post-Edits in Machine Translation

arXiv:2609.16340v1 Announce Type: new Abstract: Machine translation systems are periodically upgraded to stronger models, but the available preference signal is human post-edits of an older system's o

State of Thought Enables Endogenous Reasoning

arXiv:2609.16055v1 Announce Type: cross Abstract: Test-time compute has emerged as a major approach to improving the capabilities of Large Language Models (LLMs). However, existing test-time reasoning

Target-Language Generation in Multilingual Models: Activation Steering and Optimal Control

arXiv:2609.16967v1 Announce Type: new Abstract: Ensuring that multilingual language models generate coherent text in a specific target language is a major issue in multilingual language modeling. We d

The record is part of the task: matched-record evaluation of text classifiers across maintenance, safety and recall reporting

arXiv:2609.16267v1 Announce Type: cross Abstract: Many operational cases are documented more than once, at different workflow stages and for different purposes, yet model evaluations normally select o

There Is More to Refusal in Large Language Models than a Single Direction

arXiv:2602.02132v2 Announce Type: replace Abstract: Prior work argues that refusal in large language models is mediated by a single direction, enabling steering and abliteration. We show that this acc

Where Should a Document Live: Context, Representations, or Parameters?

arXiv:2609.17346v1 Announce Type: cross Abstract: To answer questions outside of their pre-training data, large language models (LLMs) need access to new information, which can be presented in the con

A Corpus-Aligned Uthmani-to-Standard Quranic Word Mapping and a Deterministic Recitation Validator

arXiv:2609.14967v1 Announce Type: new Abstract: Quranic text is distributed in two orthographic forms that are byte-level distinct: the Uthmani script used in every printed mushaf, and the Standard (I

AcquireBound: Runtime Authorization for Resources Acquired by AI Agents

arXiv:2609.14744v1 Announce Type: new Abstract: By acquiring compute, credentials, accounts, services, and other agents, autonomous AI agents can introduce new authority into a task. Payment, budget,

Agents

Agents are coming for video production. @PooldayAI is going for this. You prompt it once, and it edits your real footage, picks the right ge…

Agents are coming for video production. @PooldayAI is going for this. You prompt it once, and it edits your real footage, picks the right generative model for each task, and checks its own work before

agentsdair-ai--x

Applications

AlgoRAG: Retrieval-Augmented Generation for Theoretical Computer Science Education -- A Comprehensive Evaluation Framework for Algorithm Analysis and Complexity Theory

arXiv:2609.14572v1 Announce Type: cross Abstract: Teaching abstract theoretical computer science (TCS) concepts such as algorithm analysis and complexity theory is challenging because students must ha

applicationsarxiv-cs-ai

Algorithm Validation as a Policy Audit: Evidence from Race-blind Charging

arXiv:2609.13174v1 Announce Type: cross Abstract: California recently required all prosecutors in the state to conduct a 'race-blind charging' decision by reviewing case documents in which selected ra

All Learning Has an Emotional Basis, So Does Task-Oriented Dialogue

arXiv:2507.01594v2 Announce Type: replace Abstract: Task-oriented dialogue (ToD) systems aim to help users accomplish goals through natural language interaction. Beyond task success, effective ToD sys

Are explainable AI (XAI) evaluation strategies aligned? Comparing subjective, objective, and mathematical evaluation measures using saliency maps

arXiv:2504.17023v2 Announce Type: replace-cross Abstract: The evaluation of explainable AI (XAI) approaches often relies on three families of methods: subjective measures (e.g., questionnaires on trus

researcharxiv-cs-ai

Assembling the CREW: A Collaborative Multi-agent Reinforcement Learning Framework for Automated Related Work Generation

model-releasesarxiv-cs-lg

arXiv:2609.15721v1 Announce Type: new Abstract: Automatic Related Work Generation (RWG) significantly reduces the human time and effort required to author the Related Work Section (RWS) of a research

au-Elicitation: Benchmarking multi-turn entity extraction in voice agents

arXiv:2609.13602v1 Announce Type: new Abstract: Voice agents often need to collect names, addresses, identifiers, dates, and times exactly, yet end-to-end benchmarks obscure where capture fails. We in

b10981

model-releasesllama-cpp-releases

OpenVINO: optimize stateful decode and GPU MoE inference (#28638) exclude GPU/NPU failing POOL_2D case Fix pool case ggml-openvino: fix stateful decode for Gemma-4 per-layer-type head sizes ggml-openv

Beyond Accuracy: Robustness, Cost, and Governance Trade-offs for Vision-Language Models in Templated Document Extraction

arXiv:2609.15706v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used to extract structured fields from business documents, yet most evaluations report accuracy on clean

Beyond Scene Description: Multi-Agent Orchestration for Non-visual Access to Virtual Worlds

arXiv:2609.14512v1 Announce Type: new Abstract: Virtual worlds now host classrooms, meetings, conferences, shops, and social venues, and nearly every interaction they expose assumes a user who can sca

safetyarxiv-cs-ai

Bridging the Modality Gap in Long-Form Clinical Audio: A Comparative Study of Lightweight and Heavyweight End-to-End SOAP Generation

arXiv:2609.14467v1 Announce Type: cross Abstract: Automating clinical documentation from long-form doctor-patient conversations remains challenging for modern audio-language models. While cascaded ASR

researcharxiv-cs-ai

Clean Scores, Buried Evidence, and Confident Wrong: A Receipt-Based Audit of Frontier Agentic QA

arXiv:2609.15319v1 Announce Type: cross Abstract: Frontier models score well on shallow document/chart reading tasks. In a controlled data-room audit, moving evidence into buried conditions reduced ac