All entries

TF-IDF and BM25 Are Exact KL Divergences

arXiv:2609.14016v1 Announce Type: cross Abstract: TF-IDF and BM25 are two of the most widely used methods for scoring query-document relevance, yet neither has a standard probabilistic derivation that

The Agentic Company OS: Substrate Inversion for Sustained Enterprise Agent Deployment

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

arXiv:2609.13334v1 Announce Type: cross Abstract: Enterprise AI agents often succeed in a demonstration and then stall once they must operate day after day. An industry report estimates that most pilo

safetyarxiv-cs-ai

15 Sept 2026

The Attribution-Compression Frontier in Retrieval-Augmented Generation

arXiv:2609.14245v1 Announce Type: cross Abstract: Context compression reduces generator input in retrieval-augmented generation, but answer quality alone does not characterize citation attribution. We

The average-farmer illusion in language-model simulations of agricultural decisions

arXiv:2609.15038v1 Announce Type: new Abstract: Language-model agents are increasingly used as synthetic people in surveys and social simulations, yet their apparent realism is often judged from popul

The Filter Metric is Safety-Critical: Phantom Advantages in Group-Relative RL under Shaped Rewards

arXiv:2609.13866v1 Announce Type: new Abstract: Group-relative policy optimization (GRPO and descendants) can discard no-contrast rollout groups through dynamic sampling, while practical implementatio

safetyarxiv-cs-lg

The Garden of Forking Prompts: How Users Explore Narrative Space in Story Generation

arXiv:2609.14677v1 Announce Type: new Abstract: Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate storie

The Language-Energy Divide: Measuring Energy Costs of Multilingual LLM Inference

arXiv:2606.21869v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed in multilingual settings, yet the energy costs of serving these models across different

The Limits of Reference-Free Speech Quality Metrics as Evaluators and Rewards on Modern Text-to-Speech

arXiv:2609.13150v1 Announce Type: cross Abstract: Reference-free quality predictors such as UTMOS, DNSMOS and SCOREQ are the de facto automatic evaluators for text-to-speech (TTS) and are increasingly

safetyarxiv-cs-cl

The Marked Edge Walk: A Novel MCMC Algorithm for Sampling of Graph Partitions

arXiv:2510.17714v3 Announce Type: replace-cross Abstract: Novel Markov Chain Monte Carlo (MCMC) methods have enabled the generation of large ensembles of redistricting plans modeled as a graph partiti

safetyarxiv-cs-lg

The Metric Slingshot: Navigational Reuse as Width-Optimal Structural Decoupling in Continual Learning

arXiv:2603.15412v2 Announce Type: replace Abstract: The mammalian brain, most extensively studied in rodents and bats, solves an enormous variety of non-spatial cognitive tasks using neural circuitry,

The Misery of Mechanistic Interpretability: A Formal Perspective

arXiv:2609.15533v1 Announce Type: cross Abstract: Mechanistic interpretability has become the dominant lens for understanding frontier language models, as their inner workings are complex and inherent

The MODA General Attribute Suite: A Four-Track Evaluation Benchmark for Fashion Attribute Extraction

model-releasesarxiv-cs-cv

arXiv:2609.13279v1 Announce Type: new Abstract: Fashion attribute extraction is evaluated inconsistently: results are reported as single aggregate numbers across image types that pose different proble

The Router Within: Eliciting Native Skill Routing from a Frozen LLM

arXiv:2609.15982v1 Announce Type: cross Abstract: Skills extend an LLM agent beyond its parametric knowledge, and the gain they promise rests on picking the right one. Deployed harnesses route by prel

The Stochastic Deputy: Structural Tenant Isolation for Tool-Using LLM Agents

arXiv:2609.14780v1 Announce Type: cross Abstract: Multi-tenant tools commonly accept a tenant identifier and validate it against the caller's entitlement. For a large language model (LLM) agent, that

Local Ai

The Theory of Mind Utility: A Formal Account of Mentalizing

arXiv:2606.12721v3 Announce Type: replace Abstract: Inferring another person's beliefs requires reconstructing their information access history: what they encountered, in what order, from whom, and wi

local-aiarxiv-cs-ai

The Token Before the Value Is the Key: How Hybrid Architectures Organize Induction Circuits

arXiv:2609.15545v1 Announce Type: new Abstract: Hybrid language models can improve capability as well as efficiency, raising the question of how architectural complementarity becomes learned computati

The Troy Moment of AI: Why SomeWill Cheat and SomeWill Follow?

arXiv:2609.15494v1 Announce Type: new Abstract: Recent investigations of the July 2026 OpenAI--Hugging Face incident motivate two questions about agent behavior under task failure: when an assigned ta

The Universe of Universes: Benefit Yield Functions, Implosion Thresholds, and Infrastructure-Aware Optimization in Multi-LLM Systems

arXiv:2609.15314v1 Announce Type: cross Abstract: We introduce the Universe of Universes (UoU) framework, which treats the full ecosystem of major large language models (LLMs) as a structured retrieva

The University of Melbourne WMT 2026 CreoleMT Submission: A Domain-Balanced Approach to Low-Resource Pacific Creole Machine Translation

model-releasesarxiv-cs-cl

arXiv:2609.13615v1 Announce Type: new Abstract: For our submission to the WMT26 Creole Language Translation Shared Task, we focus on machine translation (MT) models for Pacific creoles: Tok Pisin, Bis

Agents

Theseus in the Graph: Towards Traceable Multi-Hop Graph Navigation

arXiv:2609.14528v1 Announce Type: new Abstract: Multi-Hop Knowledge Graph Question Answering (KGQA) tasks require models to assemble relational evidence along paths in a KG to answer natural-language

agentsarxiv-cs-cl

Thin-shell stability of Gaussian cooling: logconcave sampling with sesteric complexity from a cold start

arXiv:2609.15884v1 Announce Type: cross Abstract: We show that logconcave probability measures along the Gaussian cooling path have thin-shell stability, generalizing the thin-shell theorem. This resu

Thinking beyond the anthropomorphic paradigm benefits LLM research

arXiv:2502.09192v3 Announce Type: replace Abstract: Anthropomorphism, or the attribution of human traits to technology, is an automatic and unconscious response that occurs even in those with advanced

Thought without systematicity? Evaluating reasoning models on rule induction tasks

arXiv:2609.13948v1 Announce Type: cross Abstract: A central tenet of human cognition is systematicity, the principle that understanding one concept is inherently tied to understanding close variations

Tutorials

ThreshGuide: Class-Aware Labeled-Guided Thresholding for Semi-Supervised 3D Abdominal Multi-Organ Segmentation

arXiv:2609.14943v1 Announce Type: new Abstract: Pseudo-labeling is a strong paradigm for semi-supervised medical image segmentation, yet its effectiveness is highly sensitive to confidence thresholdin

tutorialsarxiv-cs-cv

Through the Eyes of the Beholder: Biometric and Demographic Conditioning for Multimodal Sexism Detection

arXiv:2609.15608v1 Announce Type: cross Abstract: Detecting sexism on the internet is a fundamentally subjective task; our team, VANGUARD, addresses this challenge in the EXIST 2026 Task 2 by proposin

Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarks

arXiv:2504.07099v5 Announce Type: replace-cross Abstract: Frequency-domain analysis has emerged as a powerful paradigm for time series analysis, offering unique advantages over traditional time-domain

Tutorials

TimeThink: Eliciting Compositional Reasoning in Timeseries Large Language Models

arXiv:2609.13457v1 Announce Type: new Abstract: Timeseries multimodal large language models (TS-MLLMs) have recently begun leveraging the reasoning capabilities of large language models (LLMs) for que

tutorialsarxiv-cs-ai

To Blend In, First Decouple: Rethinking Camouflage Image Generation via Context-Decoupled Representations

arXiv:2607.17768v2 Announce Type: replace Abstract: Camouflage image generation (CIG) focuses on generating visually concealed objects that seamlessly blend into their backgrounds. Existing methods ty

researcharxiv-cs-cv

To do(x) or not to do(x): Medical Image Counterfactuals for Dataset Augmentation

arXiv:2609.14124v1 Announce Type: cross Abstract: Medical image analysis is often hindered by biased datasets, which can lead to biased models and limited clinical applicability. A promising strategy

safetyarxiv-cs-ai

To Each Language Its Tokenizer: Modular Tokenizers for Efficient Multilingual LLMs

arXiv:2609.15528v1 Announce Type: new Abstract: Multilingual Large Language Models (LLMs) traditionally rely on a single vocabulary shared by all supported languages, which can lead to uneven compress

safetyarxiv-cs-cl

To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation

arXiv:2603.15159v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown strong potential for code generation, yet they remain limited in private-library-oriented code generat

Agents

Token Efficient Task Execution via Application Behavior Modeling for Web Agents

arXiv:2609.13491v1 Announce Type: new Abstract: The strong performance of AI Agents across an impressive variety of tasks is driving an unprecedented investment in agentic infrastructures, however the

agentsarxiv-cs-ai

Applications

Token Merging for Multilingual Speech Recognition: A Systematic Study Across Model Scale and Fine-Tuning

arXiv:2609.13151v1 Announce Type: new Abstract: Leading multilingual speech recognition models like Whisper transcribe diverse, low-resource languages without language-specific training but are comput

applicationsarxiv-cs-cl

Tone on a Budget: A Reference-Free Metric for Lexical Tone in Massively Multilingual Text-to-Speech

arXiv:2609.14817v1 Announce Type: new Abstract: In Yoruba, pitch alone separates oko (husband, Mid), okd{o (vehicle, Low), and okd{o (hoe, High) -- the diacritics ARE the tone marks. Yet character err

Tool Use Reduces Depth-Induced Collapse in OOD Reasoning

arXiv:2602.21061v2 Announce Type: replace Abstract: Many current paths to more advanced AI depend on the assumption that large language models (LLMs) can generalize learned relationships to solve comp

Local Ai

TopoRig: Topology-Agnostic Facial Rigging via Multi-Source Supervision

arXiv:2609.15746v1 Announce Type: cross Abstract: Automatic facial rigging across heterogeneous mesh topologies remains challenging because high-quality expression supervision is often tied to canonic

local-aiarxiv-cs-cv

TotalSynth: Robust Whole-Body Synthetic CT from MRI and CBCT

model-releasesarxiv-cs-cv

arXiv:2609.13838v1 Announce Type: new Abstract: Purpose: To develop and evaluate TotalSynth, a reusable pretrained framework for whole-body synthetic CT (sCT) generation from MRI and cone-beam CT (CBC

Touch2Trace: Tactile-Driven Imitation Learning for Dexterous Cable Tracing

arXiv:2609.15921v1 Announce Type: new Abstract: Dexterous manipulation of deformable objects demands continuous fingertip-level regulation of pressure, friction, and incipient slip. We study one of th

safetyarxiv-cs-ro

Toward a Decision-Assurance Layer for AI-Assisted Flight Planning in Air Traffic Management

arXiv:2609.13552v1 Announce Type: new Abstract: Generative AI is increasingly being used informally in Air Traffic Management (ATM) for tasks such as flight plan generation, trajectory interpretation,

safetyarxiv-cs-ai

Toward a Layer-2 Trigger for AI/ML Lifecycle Management in 6G

arXiv:2609.14517v1 Announce Type: cross Abstract: 3GPP has progressively expanded AI/ML lifecycle management in the radio access network, from one-sided model control to Release 20 support for two-sid

Toward Complete Hospital Discharge Summarization with Abstract Meaning Representation

arXiv:2609.13581v1 Announce Type: new Abstract: Discharge summaries are lengthy medical documents that summarize a hospital in-patient visit. Automatically generating them can reduce documentation bur

safetyarxiv-cs-cl

Toward Optimal Switching Regret for Multi-Armed Bandits with Oblivious Adversary

arXiv:2609.13547v1 Announce Type: new Abstract: We study switching regret in adversarial multi-armed bandits, where the learner competes with an arm sequence that changes at most S times. When S is kn

Toward Secure Code Generation: Bridging Correctness and Security via Task-Adaptive Vulnerability Modeling and Execution-Based Benchmarking

model-releasesarxiv-cs-cl

arXiv:2407.02395v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for program synthesis, yet they often generate code that is functionally plausible but inse

Agents

Toward Self-Adaptive Physical AI: Can LLM Agents Manage Long-Horizon Physical Tasks?

arXiv:2609.13436v1 Announce Type: new Abstract: Large Language Model (LLM) agents offer a promising path toward autonomously managing long-term physical tasks without human intervention. However, phys

agentsarxiv-cs-ai

Towards a knowledge-enhanced single-cell foundation model

arXiv:2609.14970v1 Announce Type: new Abstract: Single-cell foundation models (scFMs) increasingly rely on large-scale transcriptomic pretraining, yet expanding pretraining data can yield diminishing

Towards a Mechanistic Understanding of Propositional Logical Reasoning in Large Language Models

arXiv:2601.04260v2 Announce Type: replace Abstract: Understanding how Large Language Models (LLMs) perform logical reasoning internally remains a fundamental challenge. While prior mechanistic studies

Towards Anticipatory Databases Through Shared Data and Workload Semantics

arXiv:2609.14255v1 Announce Type: cross Abstract: Database management systems increasingly serve dynamic and exploratory workloads, yet many of their decisions still rely on low-level signals such as

Towards Evolving Context Parameterization for Large Language Models

arXiv:2609.14168v1 Announce Type: cross Abstract: Context parameterization enables large language models (LLMs) to internalize contexts into reusable model parameters, avoiding repeated processing acr