Search: “open-weights”

Combating Instruction Conflict via Energy-Driven Latent Conflict Detection

arXiv:2609.08646v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed with hierarchical instructions, yet they remain vulnerable to conflicts in which user directi

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CRISS: A Retrieval-Augmented AI Chatbot for Assisting Cancer Registrars

DGX agent

arXiv:2609.29075v1 Announce Type: new Abstract: Cancer registrars, including Oncology Data Specialists (ODSs), must interpret complex and frequently updated coding and staging standards. We developed

model-releasesarxiv-cs-ai

25 Sept 2026

Don't Read the Log: Execution Traces Contaminate Verifiers in Video-Generation Agents

arXiv:2609.28564v1 Announce Type: cross Abstract: Agentic video-generation systems close a loop between a generator and a verifier: an LLM plans shots, calls a text-to-video model, and a multimodal ju

IDRBench: Benchmarking the Interactive Capabilities of Deep Research Agents

arXiv:2601.06676v3 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based deep research agents perform multi-step reasoning, web exploration, and long-form report generation. In these

LLMersion: A Local-First AI Agent Framework for Low-Cost Home Language Learning toward Educational Equity

arXiv:2609.29672v1 Announce Type: new Abstract: Artificial intelligence helps education most where an essential provision has been rationed by cost. For language learners that provision is a teacher's

PROOF: Profiling Reliability of Object-Level Facts in Large Language Models

arXiv:2609.29504v1 Announce Type: cross Abstract: Aggregate factuality scores hide where a language model succeeds, which relations it confuses, and whether an answer survives innocuous changes to the

Screen Before You Serve: Simulation for Production Customer Experience AI Agents at 140M Scale

arXiv:2609.30137v1 Announce Type: new Abstract: Customer experience (CX) agents use tools and large language models to address customer requests and guide conversational interactions with an organizat

Stochastic Semantic Evidence Graphs: Uncertainty Propagation and Governance for Agentic AI

arXiv:2609.29703v1 Announce Type: new Abstract: AI-agent evaluations usually inspect a final answer, yet error may enter through evidence, retrieval, prompting, generation or decision mapping. We intr

agentsarxiv-cs-cl

Benchmarking Text-to-SQL under Role-Based Access Control

arXiv:2607.22115v2 Announce Type: replace-cross Abstract: Given a database S and a natural language question Q, text-to-SQL systems aim to generate an SQL query that correctly answers Q when executed

COMED: The Missing Middle Between Routing and Collaboration in Multi-LLM Inference

arXiv:2609.26913v1 Announce Type: cross Abstract: No single Large Language Model (LLM) is uniformly reliable across queries, motivating multi-model inference systems that either route among models or

InGuard: Towards Generalized Inner Guardrail for Safe Text-to-Image Generation

arXiv:2609.27620v1 Announce Type: cross Abstract: Modern text-to-image (T2I) models generate high-quality images from arbitrary user prompts, yet they can just as easily produce not-safe-for-work (NSF

When Entanglement Lower-Bounds Disparity: Auditing and Repairing Demographic Fairness in Audio Understanding Models

arXiv:2609.27382v1 Announce Type: cross Abstract: Speech technology penalizes some voices: recognition errs nearly twice as often for Black speakers, and accuracy declines for second-language accents

safetyarxiv-cs-cl

Local Ai

Agents That Edit Documents: Measuring Agentic PDF Forgery Against a Non-Agentic Control

arXiv:2609.23953v1 Announce Type: new Abstract: AI agents that carry a multi-step computer task through on their own became ordinary tools in the past year, and the same autonomy is available to anyon

local-aiarxiv-cs-ai

Agreement Overstates Evidence: Error Dependence in LLM Judge Consensus

arXiv:2609.22512v1 Announce Type: new Abstract: Consensus among LLM judges is often taken as strong evidence that a decision is correct. This assumes that judges make their errors independently. In pr

Component Type, Not Reconstruction Error, Predicts Attention Quantization Sensitivity

arXiv:2609.26173v1 Announce Type: new Abstract: Many post-training quantization (PTQ) methods use layer-wise reconstruction, second-order proxy objectives, or activation-aware transformations to reduc

Hill Sampling for Test-Time Scaling: A Simple and Better Alternative to Repeated Sampling, Evolution, and Training

arXiv:2609.25510v1 Announce Type: new Abstract: Large language models (LLMs) can improve solutions to verifiable scientific and algorithmic problems by spending additional computation at test time. Re

Same Quantity, Different Answer: Numerical Representation Invariance in Language Models

arXiv:2609.25009v1 Announce Type: new Abstract: Numerically equivalent word problems should yield the same canonical answer whether a quantity is written as a decimal, fraction, percentage, number wor

Does the Truthfulness Signal Survive Code-Mixing? Probing Hidden States for Hallucination Detection in Hinglish

arXiv:2609.22138v1 Announce Type: new Abstract: Hidden-state hallucination probing - training a linear classifier on an LLM's internal activations to detect whether a generated answer is faithful to t

ECP-Bench: Benchmarking and Learning Entertainment Content Promotion with Foundation Models

arXiv:2609.22150v1 Announce Type: cross Abstract: Content promotion spans a broad set of skills, from understanding content to forecasting its market reception. However, LLMs' ability to support such

Fairness Beyond Anonymization? Demographic Leakage in German LLM-Generated Resumes

arXiv:2609.22188v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into AI-assisted hiring pipelines, including automated resume generation and screening. Under t

From Tables to Quantified Statements: Evaluating LLM Inference Generation through Executable Verification

arXiv:2609.23966v1 Announce Type: new Abstract: LLMs can generate fluent descriptions from tables, but their outputs may remain logically unsupported by the structured data. We introduce STAT-TO-TEXT,

researcharxiv-cs-cl

Tutorials

LLM-Based FORM Code Generation with Verification-Driven Fine-Tuning

arXiv:2609.23367v1 Announce Type: cross Abstract: FORM is a domain-specific symbolic manipulation language widely used in particle physics for processing the very large algebraic expressions arising f

tutorialsarxiv-cs-cl

Local Ai

Measuring the Assistant's Harmlessness Preferences on the User Turn

arXiv:2609.23935v1 Announce Type: new Abstract: Post-training turns a general next-token predictor into a chat model with a persistent assistant persona. If that persona is a character the model plays

local-aiarxiv-cs-cl

On Mitigation of Subliminal Learning in Large Language Models

arXiv:2609.22215v1 Announce Type: new Abstract: Knowledge distillation can transmit unintended behavioral traits from a teacher model to a student through training data that appear semantically unrela

Prior-Amortized In-Context Bayesian Inference for Generalized Linear Mixed-Effects Models

arXiv:2609.24422v1 Announce Type: new Abstract: Hierarchical data is ubiquitous in the empirical sciences and is most commonly analyzed with generalized linear mixed-effects models (GLMMs). Bayesian i

Recognition, Simulation, and Refusal: A Contamination-Aware Study of Classic Psychological Effects in LLM Agents

arXiv:2609.22090v1 Announce Type: new Abstract: An LLM producing the response pattern associated with a human psychological effect is not the same claim as the LLM possessing that bias. We present Psy

Time-Incremental Continued Pretraining of LLMs: Knowledge Updates Without Catastrophic Forgetting

arXiv:2609.23916v1 Announce Type: new Abstract: Large language models (LLMs) drift out of date the moment their pretraining ends, yet retraining from scratch is prohibitively expensive. Continued pret

When and Why Do Linear Bias Probes Fail? A Geometric and Statistical Theory of Bias Detectability in Large Language Model Representations

arXiv:2609.22337v1 Announce Type: cross Abstract: Linear probing is the standard instrument for detecting social biases in the hidden representations of large language models. Yet reported probe accur

safetyarxiv-cs-lg

When Who You Are Can Change the Code You Get: A Study of Persona-Induced Bias in LLM Code Generation

arXiv:2609.22102v1 Announce Type: cross Abstract: Large Language Models (LLMs) are widely used as programming assistants, yet it remains unclear whether and how user's demographic information impacts

CESBench: Benchmarking Large Language Models on Cryptographic Engineering Security for IoT Devices

arXiv:2609.21344v1 Announce Type: cross Abstract: For Internet of Things (IoT) devices, a secure algorithm alone is not enough: an attacker with physical access can attack the implementation directly,

Do Personality-Tuned LLMs Make Better Social Agents?

arXiv:2609.21857v1 Announce Type: cross Abstract: LLMs are increasingly used in social simulations for socially interactive agents and robots, offering more flexibility than rule-based systems. Howeve

Hardware

How Much of a Real Workload Can LLM-Generated GPU Kernels Actually Reach?

arXiv:2609.21058v1 Announce Type: cross Abstract: Language models can now write GPU kernels that outperform PyTorch. We evaluate five model configurations on KernelBench level 1 and find that a fronti

hardwarearxiv-cs-ai

K2-V2: A 360-Open, Reasoning-Enhanced LLM

arXiv:2512.06201v3 Announce Type: replace Abstract: We introduce K2-V2, a 360-open LLM built from scratch as a superior base for reasoning adaptation, in addition to functions such as conversation and

safetyarxiv-cs-lg

NemotronLabs VoiceChat: An Open Full-duplex Speech-to-Speech Model with Tool Calling Capabilities

arXiv:2609.21967v1 Announce Type: cross Abstract: We introduce NemotronLabs VoiceChat, an open full-duplex speech-to-speech model with native tool-calling capabilities. NemotronLabs VoiceChat combines

Steering LLMs Responses Towards Moral Foundations on the Norwegian MFQ-30

arXiv:2609.21636v1 Announce Type: cross Abstract: Recent work applies human psychometric questionnaires to large language models to elicit moral and value profiles, but it is not clear whether these i

Chain-of-Thought Entropy as a Reliability Signal: A Preregistered Reproduction

arXiv:2609.19606v1 Announce Type: new Abstract: This empirical study is an independent reproduction of the dissociation Zhao reported in 2026. The shape of a large language model's chain-of-thought en

CliniCIRCA: A Modular LLM Framework for Constructing Longitudinal Mental Health Patient Journeys from Raw EHR Narratives

arXiv:2609.19585v1 Announce Type: cross Abstract: In mental health care, reasoning over patient journeys is a key task for clinicians. Yet these journeys, encompassing a longitudinal progression of bi

From Intent to Action: Benchmarking LLM Safety in Vehicle Voice Command Authorization

arXiv:2609.19630v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into vehicle voice assistants. But linking natural-language requests to vehicle functions creat

PetriBench: Benchmarking LLM Reasoning over Dynamic State Spaces

arXiv:2609.19883v1 Announce Type: cross Abstract: Characterizing LLM reasoning remains an open challenge, as many existing benchmarks isolate specific reasoning skills, rely on external knowledge, or

Quantifying Overclaiming Propensity in Frontier LLM Agents

arXiv:2609.20812v1 Announce Type: cross Abstract: Frontier coding agents are increasingly trusted to work autonomously for long periods, yet an agent's final response is often the only account of that

AfriSyCo: Measuring Assertive Framing, Verification, and Wording Sensitivity Around African-Language Content

arXiv:2609.17853v1 Announce Type: cross Abstract: AfriSyCo studies answer switching around African-language factual content with two complementary layers: native-language follow-ups and a controlled c

BENCHCOMPASS: From Scores to Signals for Training and Harness Decisions in Payment-Domain LLMs

arXiv:2609.18270v1 Announce Type: new Abstract: Payment operations are a critical financial infrastructure, but the value of large language models in this domain remains unclear because payment rules

From a River in Gilead to the Inference Distributions of Large Language Models: Covert Dialect Bias and Linguistic Profiling at Scale

arXiv:2609.18068v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains such as housing screening. While alignment techniques mitigate explicit

safetyarxiv-cs-ai

Function Lives Where Variance Doesn't: Task-Weighted Charts of a Language Model's Computation

arXiv:2609.18989v1 Announce Type: new Abstract: How many dimensions does a language model's computation actually use? The question is ill-posed until one names a functional. Task-weighted charts make

How Much is a Human Right Worth? ECtHR-NPD: A Benchmark for Predicting Non-Pecuniary Damage Awards

arXiv:2609.18908v1 Announce Type: new Abstract: Existing legal benchmarks cover diverse tasks, while continuous monetary remedies remain comparatively underexplored. We introduce ECtHR-NPD, to the bes

Market Signal Injection: Adversarial Context Manipulation of LLM Pricing Agents

arXiv:2609.18357v1 Announce Type: new Abstract: Large language model (LLM) pricing agents may respond to how market data is presented, even when its numerical values remain unchanged. We introduce mar

Rethinking Domain Specialization for Open-Ended Scientific Reasoning in Astronomy Language Models

arXiv:2609.17644v1 Announce Type: cross Abstract: Domain-specialized language models are widely used for scientific question answering, but stronger general-purpose systems raise a sharper question: w

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