Search: “llm”

DisclosureBeta: A Measurement-Channel Theory for Regime-Conditioned Betas from LLM-Read Risk Disclosures

arXiv:2609.02900v1 Announce Type: cross Abstract: The problem is the beta a desk needs when a firm's price history is too short to trust: an S-1 filer, a recent listing, or a name just past a regime b

researcharxiv-cs-cl

4 Sept 2026

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GeoNatureAgent Benchmark: Benchmarking LLM Agents for Environmental Geospatial Analysis Across Frontier and Open-Weight Foundation Models

DGX agent

arXiv:2606.12821v2 Announce Type: replace Abstract: Environmental scientists spend disproportionate effort on data wrangling rather than analysis. New AI agents can be a helpful tool, but no benchmark

model-releasesarxiv-cs-ai

4 Sept 2026

LLM as GNN: Graph Vocabulary Learning for Text-Attributed Graph Foundation Models

arXiv:2503.03313v4 Announce Type: replace-cross Abstract: Text-Attributed Graphs (TAGs), where each node is associated with text descriptions, are ubiquitous in real-world scenarios. They typically ex

safetyarxiv-cs-cl

4 Sept 2026

SLIDEFORGE: An LLM Agent for Controllable Editing of Slides as Structured Artifacts

arXiv:2609.03109v1 Announce Type: new Abstract: Current AI agents compellingly describe slides. However, AI-assisted slide editing requires more than understanding: the output must retain layout, styl

agentsarxiv-cs-cv

4 Sept 2026

Are Near-Tied LLM Rankings Robust to Family-DIF-Guided Benchmark Recomposition?

arXiv:2609.00482v1 Announce Type: new Abstract: Small leaderboard gaps are often interpreted as evidence that one language model is better than another, but their sign may depend on which benchmark it

2 Sept 2026

AutoXRD: Autonomous LLM Agents and Comprehensive Evaluation for Powder Diffraction Analysis

arXiv:2609.00070v1 Announce Type: cross Abstract: Powder X-ray diffraction (XRD) is central to materials characterization, yet reliable end-to-end automation remains challenging. An XRD agent must int

2 Sept 2026

REAL-Q: E2E LLM Quantization via Dynamic Gradient Descent

arXiv:2609.00049v1 Announce Type: cross Abstract: Post-training quantization (PTQ) is essential for deploying large language models (LLMs) under strict resource constraints. State-of-the-art PTQ metho

2 Sept 2026

Can LLM Agents Discover? Evaluating Creativity on ML Engineering Tasks

arXiv:2608.30047v1 Announce Type: new Abstract: Recent AI systems promise autonomous scientific discovery, claiming to discover algorithms and produce research papers, yet understanding whether they e

Different Demographic Cues Yield Inconsistent Conclusions About LLM Personalization and Bias

arXiv:2601.18486v3 Announce Type: replace Abstract: Demographic cue-based evaluation is widely used to study how large language models (LLMs) adapt their responses to signaled demographic attributes w

E-Commerce Bench: Evaluating LLM Agents on Long-Horizon Autonomous Business Operation

arXiv:2608.30730v1 Announce Type: cross Abstract: Long-horizon agentic tasks go beyond chaining short tasks over more interaction turns. Their evolving dynamic environments and long-range dependencies

Error-Type-Aware Loss Reweighting for Robust Named Entity Recognition with Noisy LLM Labels

arXiv:2608.30827v1 Announce Type: new Abstract: Large language models are increasingly used to annotate datasets for training smaller, task-specialized models such as named entity recognition. While t

researcharxiv-cs-cl

Evaluating LLM-based AI agents integrated with materials synthesis tools: the case of atomic layer deposition

arXiv:2608.29309v1 Announce Type: cross Abstract: This work provides an overview of the different strategies that can be used to evaluate the performance of AI models and agents based on large languag

How You Ask Shapes What You Get: A Theory-Seeded Measurement of Articulation in Advice-Seeking LLM Conversations

arXiv:2608.29591v1 Announce Type: new Abstract: Users articulate the same advice-seeking request in different ways: some specify detailed constraints, others gesture at a vague need. Prior work treats

researcharxiv-cs-cl

Influence Is Not Authority: When Causal Guardrail Signals Make Legitimate Tool Use Look Like an Attack in Tool-Using LLM Agents

arXiv:2608.29942v1 Announce Type: cross Abstract: The key limitation of current state-of-the-art influence-based guardrails is that they do not reliably distinguish a legitimate, user-authorized actio

JFTA-Bench: Evaluate LLM's Ability of Tracking and Analyzing Malfunctions Using Fault Trees

arXiv:2603.22978v2 Announce Type: replace Abstract: In the maintenance of complex systems, fault trees are used to locate problems and provide targeted solutions. To enable fault trees stored as image

RegDivergence-101: An LLM Benchmark for Cross-Jurisdiction Regulatory Contradiction Detection in Life Sciences

arXiv:2608.28607v1 Announce Type: new Abstract: Pharmaceutical sponsors developing a drug for both the United States and the European Union must reconcile guidance issued independently by the FDA and

Selective Forgetting: A Graph-Based Memory Framework for Long-Term LLM Agents

arXiv:2608.28978v1 Announce Type: new Abstract: Knowledge graphs have been proposed as a structured alternative to flat retrieval-augmented generation for long-term agent memory, on the assumption tha

TRACER: Per-Tool Context Retention for LLM Agents via Consequence-Attributed Reinforcement Learning

arXiv:2608.29363v1 Announce Type: new Abstract: Enterprise data agents answer business queries by chaining many tool calls over multiple reasoning steps, routinely accumulating hundreds of thousands o

safetyarxiv-cs-ai

Training and Agentic Inference Strategies for LLM-based Manim Animation Generation

arXiv:2604.18364v2 Announce Type: replace Abstract: Generating programmatic animation using libraries such as Manim presents unique challenges for Large Language Models (LLMs), requiring spatial reaso

Validating FKG.in: Soundness Assessment in LLM-Augmented Indian Food Knowledge

arXiv:2608.29249v1 Announce Type: new Abstract: The online culinary ecosystem is increasingly populated by recipe content generated, modified, or summarized by Large Language Models (LLMs). While ofte

When Do Larger Batches Help Scale LLM Reinforcement Learning?

arXiv:2608.29296v1 Announce Type: cross Abstract: Larger batches reduce the variance of stochastic gradients per update and are therefore often expected to accelerate training. Yet whether this statis

You Shouldn't Have Asked: A Pragmatics-Inspired Taxonomy for Evaluating LLM Refusals

arXiv:2608.30856v1 Announce Type: new Abstract: Refusals are often treated as face-threatening acts in pragmatics because they can challenge the requester's socially claimed self-image. Large language

safetyarxiv-cs-cl

D-TAIA: Domain-Aware LLM Adaptation for Multi-Task Predictive Process Monitoring

model-releasesarxiv-cs-lg

arXiv:2608.28236v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) enables organizations to forecast future process behavior, such as the next activity and remaining time of ongoing c

31 Aug 2026

GRACE:Gradient-guided Coreset Selection for LLM Unlearning

arXiv:2608.28361v1 Announce Type: cross Abstract: Machine Unlearning methods for Large Language Models typically assume pre-specified forget and retain sets. In realistic settings, however, requests m

researcharxiv-cs-lg

31 Aug 2026

The Instability of Safety: How Random Seeds and Temperature Expose Inconsistent LLM Refusal Behavior

arXiv:2512.12066v3 Announce Type: replace-cross Abstract: Current safety evaluations of large language models rely on single-shot testing, implicitly assuming that model responses are deterministic an

31 Aug 2026

UPS Fuse Exploded While Running an LLM

I was running Ollama with Maxwell 1500, using a 65,536-token context window, through Zoo Code inside VS Code. I asked the model to analyze a folder containing some pretty simple code. It spent around

model-releasesr-ollama

29 Aug 2026

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air

arXiv:2507.11515v2 Announce Type: replace-cross Abstract: Operating Large Language Models (LLMs) on edge devices is increasingly challenged by limited communication bandwidth and strained computationa

safetyarxiv-cs-ai

Local Ai

DSA: Evidence-Aware LLM-Agent Orchestration for Multi-Market Stock Research

arXiv:2608.26990v1 Announce Type: new Abstract: Large language models can summarize financial information, but an operational stock-research system must first assemble heterogeneous evidence, expose u

local-aiarxiv-cs-ai

From SQL to Knowledge Graphs: An LLM-Driven Multi-Agent Approach with Data Schema Improvement

arXiv:2608.26117v1 Announce Type: cross Abstract: RDBMS (Relational Database Management System) databases face several limitations, including slow execution with multi-hop queries and a lack of explai

Knowing When Not to Reuse: Conditional Experience Transfer in Autonomous LLM Post-Training

arXiv:2608.26730v1 Announce Type: new Abstract: Large language models offer broad capabilities, but adapting them to evolving domains, tools, and requirements often entails repeated post-training. Aut

Knowledge-Verified Emergent Deception in LLM Agents Under Conflicting Incentives

arXiv:2608.26372v1 Announce Type: cross Abstract: Large language models are increasingly deployed as autonomous agents serving users on behalf of companies, placing them in settings where user and dep

LLM Analysis of 150+ years of German Parliamentary Debates on Migration Reveals Shift from Post-War Solidarity to Anti-Solidarity in the Last Decade

arXiv:2509.07274v4 Announce Type: replace Abstract: Migration has been a core topic in German political debate, from postwar expellee displacement to labor migration and recent refugee movements. Larg

PLCBench: Can Autonomous LLM Agents Turn PLC Access into Sustained Physical Impact?

arXiv:2608.26882v1 Announce Type: cross Abstract: Industrial control systems (ICSs) rely on programmable logic controllers (PLCs) to connect networked computation with physical control. Tool-using lar

Local Ai

Standalone LLM and a Pre-specified Agentic Pipeline for Explaining ICU Mortality Predictions: a Feasibility Study on the eICU Demo Dataset

arXiv:2608.26109v1 Announce Type: new Abstract: Machine-learning models can predict ICU mortality accurately, but feature-attribution methods alone rarely provide the clinical narrative needed for bed

local-aiarxiv-cs-ai

Zero-Shot Self-Orchestration with Ledger-Based Control for Improved LLM Coding Performance

arXiv:2608.26480v1 Announce Type: cross Abstract: Multi-agent large language model systems are widely reported to beat single-model baselines, but the evidence is mixed, and comparisons are usually co

Learning to Prompt: Improving Student Engagement with Adaptive LLM-based High-School Tutoring

arXiv:2606.20138v2 Announce Type: replace-cross Abstract: LLMs can personalize education, although current static-prompt tutoring systems struggle to adapt to diverse academic disciplines. We develop

27 Aug 2026

Local Ai

Localize-Then-Decide Guarantees for LLM Judgments

arXiv:2608.25824v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as evaluators to assess output quality and preference alignment, yet providing reliable guarantees of

local-aiarxiv-cs-cl

27 Aug 2026

SHIFT-LLM: Distribution Shift Correction in Depth-Pruned LLMs

model-releasesarxiv-cs-cv

arXiv:2608.25068v1 Announce Type: new Abstract: Depth pruning removes entire Transformer blocks to reduce the inference cost of large language models, but disrupts the hidden-state distributions expec

27 Aug 2026

Ad Insertion in LLM-Generated Responses

arXiv:2601.19435v2 Announce Type: replace-cross Abstract: Sustainable monetization of large language models (LLMs) remains a critical open challenge. Traditional search advertising, which relies on st

26 Aug 2026

LLM-Guided Contextual Action Evaluation for Operational Decisions in Industrial Processes

arXiv:2608.24156v1 Announce Type: cross Abstract: Industrial actor--critic methods usually represent continuous actions as anonymous numerical coordinates. They must therefore learn from limited inter

safetyarxiv-cs-ai

26 Aug 2026

MARS: Multi-Specialist LLM Relay System for Competitive Programming

arXiv:2608.23918v1 Announce Type: new Abstract: Large Language Models excel at code generation, yet competitive programming exposes a persistent failure mode: existing multi-agent pipelines distribute

26 Aug 2026

Beyond Benchmarks: LLM Evaluation with an Anthropomorphic and Lifecycle-oriented Roadmap

arXiv:2508.18646v3 Announce Type: replace Abstract: Despite their rapid advancement, large language models (LLMs) suffer from a critical disconnect between benchmark scores and real-world utility. Cur

Forgotten in Weights, Recovered by Tools: Agentic Tool Unlearning for LLM Agents

arXiv:2608.21544v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as tool-augmented agents, where responses can depend on tool calls and external observations ra

From Mastery Profile to Simulated Response: Stochastic Student Knowledge Graphs (SSKG) for Faithful LLM Student Simulation

arXiv:2608.21668v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate students at different mastery levels. These simulations can generate synthetic training d

Hierarchy-Aware Supervised Uncertainty Estimation for Black-box LLM Taxonomic Reasoning

arXiv:2608.22839v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for scientific decision support, yet reliable confidence estimation remains difficult in black-box

Improving O-RADS Risk Stratification from Ultrasound Reports: A Comparative Evaluation of Hybrid versus End-to-End LLM Reasoning Strategies

arXiv:2608.23061v1 Announce Type: new Abstract: Background: Automating clinical guideline-based decision-making with large language models (LLMs) remains challenging because of reliability, hallucinat

LLM Evaluation on Unseen Questions: Contextual Multidimensional IRT Model

arXiv:2608.22295v1 Announce Type: cross Abstract: Evaluation of large language models (LLMs) increasingly requires predicting how a model will perform on new questions or tasks before collecting large

Tutorials

LLM Pedagogical Behavior in AI Tutoring Interactions

arXiv:2608.22993v1 Announce Type: new Abstract: Students increasingly use LLMs as tutors for coursework and problem solving. Little is known about the level of assistance LLMs provide when students us

tutorialsarxiv-cs-cl