Search: “llm”

PolERo: Studying Political Evasion in Romanian

arXiv:2609.02391v1 Announce Type: cross Abstract: Political evasion refers to responses that engage with a question while withholding the requested information. Recent NLP work frames political evasio

Post-Training Ternarization of Qwen3-4B Capability, Effective Bit Budget, Storage Compression, and Deployment

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DGX agent

arXiv:2609.01962v1 Announce Type: new Abstract: Ultra-low-bit language models can reduce storage and memory bandwidth, but a nominal '1.58-bit' label does not fully describe the stored representation,

model-releasesarxiv-cs-ai

3 Sept 2026

Privacy Washing: Detecting Internal Contradictions in Privacy Policies

arXiv:2609.02055v1 Announce Type: cross Abstract: Privacy policies may contain internal contradictions in which commitments are undermined by practices documented elsewhere in the same policy. We oper

safetyarxiv-cs-cl

Scalable Direction-Following TTS via Voice Impression-Guided Pseudo Triplet Construction

arXiv:2609.02623v1 Announce Type: cross Abstract: Voice actors often re-read the same script while modifying their delivery in response to performance directions. We study this setting as direction-fo

safetyarxiv-cs-cl

Scalable Kronecker-Fisher Approximation: Efficient Hessian Analysis for Billion-Parameter Language Models Compression

arXiv:2609.02451v1 Announce Type: cross Abstract: In this paper, we propose a scalable Kronecker-based approximation that captures cross-layer interactions without storing the entire Fisher matrix, en

Sparse Readout Prism: Explaining Logit-Lens Scores in Features Instead of Tokens

arXiv:2609.01936v1 Announce Type: cross Abstract: A language model's prediction of its next token develops across layers, and lens methods track this process by decoding intermediate hidden states int

SpecMine: A Large-Scale Corpus of Spec-Driven Development Artifacts

arXiv:2608.25202v3 Announce Type: replace-cross Abstract: Spec-Driven Development (SDD) is a fast-emerging practice in which a structured natural-language specification, written by a developer, or (mo

agentsarxiv-cs-ai

TalkFa: A Unified Benchmark for Farsi Dialogue Generation and Understanding

arXiv:2609.01810v1 Announce Type: new Abstract: Farsi, spoken by more than 120 million people, lacks a comprehensive benchmark for dialogue generation and understanding. We introduce TALKFA, a unified

TikZilla: Scaling Text-to-TikZ with High-Quality Data and Reinforcement Learning

arXiv:2603.03072v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to assist scientists across diverse workflows. A key challenge is generating high-quality figures

Untangling the Mechanisms of Misleading Context in Medical Question Answering

arXiv:2609.02754v1 Announce Type: cross Abstract: Large language models now answer medical questions with expert-level performance. However, the context these systems act on can be misleading, and mis

What Is Worth Representing? Representational Empowerment for Continual Model Construction

arXiv:2609.02322v1 Announce Type: cross Abstract: The first problem of modeling the world is not just estimating the right parameters or causal structure, but deciding what should be represented at al

agentsarxiv-cs-ai

Local Ai

Zeta-Lite: A Concurrent, Branchable In-Browser SQL Database for Agentic Memory

arXiv:2609.01818v1 Announce Type: cross Abstract: The browser has become a first-class database host: applications increasingly want to store, query, and reason over structured data entirely on the cl

local-aiarxiv-cs-ai

Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients

arXiv:2606.18216v2 Announce Type: replace Abstract: Knowledge distillation transfers a teacher's competence to a small student but is brittle in the small-student regime: forcing the student to imitat

A Checklist to assess the energy and carbon impacts of ML/AI applications in Earth System Modeling

arXiv:2609.00847v1 Announce Type: cross Abstract: As machine learning and artificial intelligence find their way into nearly every aspect of climate, weather, and Earth system modeling, it is worth pa

A Hybrid Insider Threat Detection Framework Combining Multi-Agent Simulation, Layered SIEM Correlation, and Theory-of-Mind Reasoning

arXiv:2601.04243v2 Announce Type: replace-cross Abstract: This paper presents a hybrid insider threat detection framework for enterprise environments, integrating multi-agent simulation, layered SIEM

agentsarxiv-cs-ai

A systematic Approach to constructing a Chance-and-Risk Matrix for Semiconductor Supply Chains

arXiv:2609.01563v1 Announce Type: new Abstract: Semiconductor supply chains face escalating risks from geopolitical tensions, geographic concentration, and rapid technological shifts, yet no scalable

Adapting Without Gradients: Affine Statistics Transport and What Its Certificate Can Tell You

arXiv:2609.00374v1 Announce Type: cross Abstract: Test-time adaptation (TTA) typically assumes that model parameters can be updated at inference time. This assumption is restrictive for inference-only

ARISE-RL: Agentic Rubric-Grounded Iterative Self-Evolution with Reinforcement Learning

arXiv:2609.01058v1 Announce Type: new Abstract: Training open-ended agents via reinforcement learning (RL) is hindered by the lack of verifiable gold answers and scalable rubrics. Moreover, even near

Bandits in Prod: Hyperparameter Optimization at Inference Time

arXiv:2609.01335v1 Announce Type: cross Abstract: Many production systems can assess a configuration only by using it on live requests and observing noisy feedback. Modern agentic systems are a promin

Beneath the Diff: Diagnosing and Mitigating Algorithmic Mode Collapse in Code-Level Autonomous Research Loops

arXiv:2609.00077v1 Announce Type: new Abstract: Code-level autonomous research loops (ARLs) have recently emerged as a concrete object of study in automated machine learning research. In such loops, a

agentsarxiv-cs-cl

Beyond AHI: An Interpretable Causal-Discovery-Guided Framework for Sleep Recovery in Connected Health

arXiv:2606.18506v2 Announce Type: replace Abstract: Objective sleep assessment relies on polysomnography (PSG), yet clinical impact is often better reflected in patient-reported outcomes (PROs) such a

safetyarxiv-cs-lg

Can Large Language Models Forecast What Researchers Study Next?

arXiv:2609.00747v1 Announce Type: new Abstract: Large language models increasingly generate research ideas, yet judging their novelty or feasibility at generation time does not establish whether they

Local Ai

Causal Probing for Internal Visual Representations in Multimodal Large Language Models

arXiv:2605.05593v2 Announce Type: replace Abstract: Despite the remarkable success of Multimodal Large Language Models (MLLMs) across diverse tasks, the internal mechanisms governing how they encode a

local-aiarxiv-cs-ai

Compressing AI Traffic: Standardized Neural Network Coding of Visual-Token Representations in Split Vision-Language Inference

model-releasesarxiv-cs-cv

arXiv:2609.01200v1 Announce Type: new Abstract: When the visual encoder and the language decoder of a vision-language model (VLM) run on different compute nodes, the intermediate visual-token embeddin

Conversation Coach: A Voice-enabled AI System that Helps Practice Difficult Workplace Conversations

arXiv:2609.00441v1 Announce Type: new Abstract: Effective manager-employee communication is critical for retaining high performers and developing underperformers, yet training managers in these skills

CRAFT: Fine-Tuning Pre-hoc Explainability in AI-native 6G RAN

arXiv:2609.00590v1 Announce Type: new Abstract: The next generation of mobile networks is envisioned as fully AI-native, with AI-RAN architectures embedding small language models (SLMs) to perform rea

safetyarxiv-cs-lg

Defense-as-Skill: Evolving Runtime Guard Skill for Skill-Augmented Agents

arXiv:2609.01487v1 Announce Type: cross Abstract: Skill-augmented agents load reusable skills as persistent runtime context, improving task performance but also giving malicious skills a durable chann

Dependency-Aware Chain-of-Thought Compression for Financial Reasoning

arXiv:2609.00413v1 Announce Type: new Abstract: Chain of thought prompting improves complex reasoning, but its long intermediate traces create substantial inference cost and hinder practical deploymen

DISTAL: Distillation and Self-Supervised Pretraining for Structure-Agnostic Materials Property Prediction

arXiv:2609.00059v1 Announce Type: cross Abstract: Materials property prediction remains difficult in low-data settings, where many target properties are supported by only a limited number of labeled s

Few-Shot Out of Domain Intent Detection with Covariance Corrected Mahalanobis Distance

arXiv:2609.00961v1 Announce Type: new Abstract: Conversational agents like chatbots and voice assistants are trained to understand and respond to user intents. On encountering an utterance with an int

FinLifeBench: Exhaustive Life-Event History and Financial-State Reconstruction from Longitudinal Banking Dialogue

arXiv:2609.01198v1 Announce Type: new Abstract: Repeated banking interactions require assistants to maintain complete, current, and traceable customer records as life changes emerge incidentally in ro

FractalNet-Based Heterogeneous Federated Learning for Orbital Edge Intelligence in Satellite Mega-Constellations: A Wildfire Case Study

arXiv:2609.00875v1 Announce Type: new Abstract: Satellite mega-constellations are emerging as large-scale sensing, communication, and computation fabrics, yet their learning architectures remain large

From Confusion to Clarity: Confusion-Aware Retrieval and Knowledge Injection for Text Classification

arXiv:2609.01564v1 Announce Type: cross Abstract: Large language models (LLMs) struggle to classify text into taxonomies with many semantically similar labels, as the distinctions are domain-specific

Good Memory Has ECC: Evaluating the Memory of Vision-Language Models Beyond Accuracy

arXiv:2609.00103v1 Announce Type: cross Abstract: Memory is widely viewed as an important unsolved problem for LLMs and VLMs, and current benchmarks typically evaluate it by testing accuracy over long

H2Table: Hierarchical Hypergraph-Enhanced Large Language Models for Complex Table Reasoning

arXiv:2609.01216v1 Announce Type: new Abstract: Tables are ubiquitous across diverse domains, yet reasoning over them remains a significant challenge for modern large language models (LLMs). Current a

IntroConformal: Conformal Factuality Guarantees for Large Vision-Language Models via Introspective Signals

arXiv:2609.01375v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved strong multimodal performance, yet ensuring the factual correctness of generated content remains ch

Joint Training Is Not Enough: Conditioned Cross-Granularity Training for Multimodal Document Understanding

arXiv:2609.00756v1 Announce Type: new Abstract: The Mutual Reinforcement Effect (MRE) asks whether a fine, span-level and a coarse, document-level task help each other when one model handles both. We

Latent Mechanisms of Language Control in Multilingual Language Models

arXiv:2609.00325v1 Announce Type: new Abstract: Multilingual large language models can exhibit unintended code-switching -- unnecessarily alternating between languages during generation. We present a

MIDR: Enrichment-Augmented Indexing for Multimodal Document Retrieval

arXiv:2609.01316v1 Announce Type: cross Abstract: Retrieval over visually rich documents has a representation problem: important content often lives in tables, charts, figures, and layout relations th

Neural Symbollic Regression Using Deep Learning and Sparse Modelling

model-releasesarxiv-cs-lg

arXiv:2609.01102v1 Announce Type: new Abstract: Symbolic Regression (SR) seeks to find succinct mathematical expressions that represent the fundamental relationships within data, providing interpretab

On the Human and Computer Alignment of Attribute-Based Music Matches

arXiv:2609.00987v1 Announce Type: cross Abstract: Recent advances in generative AI are raising ethical concerns regarding the originality of generated content and the potential replication of training

PersuaRL: Reinforcement Learning-Driven Multi-Expert Selection for Persuasive Dialogue Generation in Insurance

arXiv:2609.01188v1 Announce Type: new Abstract: Large Language Models (LLMs) are revolutionizing digital communication by powering conversational agents deployed across domains such as customer servic

Local Ai

Restrict, Don't Retrain: Inference-Time VLM Guidance for Zero-Shot Aerial Segmentation

arXiv:2609.00628v1 Announce Type: cross Abstract: Global welfare often depends on the correct interpretation of aerial and satellite imagery. Acting on such imagery (mapping flooded ground, crop exten

local-aiarxiv-cs-ai

Retrieved but not ranked: surface-form bias in structural retrieval, from mathematics to agent trajectories

arXiv:2609.01556v1 Announce Type: cross Abstract: We evaluate embedding retrieval where surface form and meaning are pulled apart on purpose: retrieving items that share underlying structure but not w

SciTrue: Reliable Scientific Claim Validation with Frontier and Open Language Models at the NTCIR SciClaimEval Task

arXiv:2609.00654v1 Announce Type: new Abstract: We describe the SciTrue team's participation in both subtasks of the NTCIR-19 SciClaimEval task~ite{sciclaimeval}, which asks systems to verify scientif

SCoNE: Selective Context-aware Neuron Editing for Robust Retrieval-Augmented Generation

arXiv:2609.00689v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is highly sensitive to retrieval noise: when retrieved documents mix informative and irrelevant context, LLMs are e

SDARE-Bench: Evaluating Large Language Models on Conversational Stigma Detection and Response in Dyadic and Group Dialogue

arXiv:2609.01548v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used in advice seeking and decision making that may affect social judgements. Despite stigma's profound ef

SlideBank: A Persistent Hierarchical Evidence Bank for Consistent Whole-Slide Reasoning

arXiv:2609.00342v1 Announce Type: new Abstract: Whole-slide images (WSIs) are challenging for vision-language reasoning because diagnostically relevant morphology is sparse, heterogeneous, and distrib