Search: “llm”

DI-Bench: Systematically Generating In-Domain Data Intelligence Benchmarks for Enterprise Agents

arXiv:2609.05776v1 Announce Type: new Abstract: Evaluating enterprise agents on domain-specific benchmarks is critical, yet public benchmarks rarely evaluate whether agents can integrate business know

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Model Releases

Do Web Agents Investigate Before They Decide?

DGX agent

arXiv:2602.05354v3 Announce Type: replace Abstract: Autonomous web agents are increasingly deployed in moderation and policy enforcement, where correct decisions often depend on evidence that is not i

model-releasesarxiv-cs-ai

10 Sept 2026

DSAEval: Evaluating Data Science Agents on a Wide Range of Real-World Data Science Problems

arXiv:2601.13591v3 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-

Evidence-Grounded Retrieval for Investigation Hunt Lead Generation from CTI Reports

arXiv:2609.08790v1 Announce Type: cross Abstract: Threat hunting increasingly depends on converting unstructured knowledge (e.g., Cyber Threat Intelligence reports) into actionable hunt leads: concise

From Retrieval to Weights: Parametric Individualization of Small Language Models with Individual Text Corpora

arXiv:2609.10155v1 Announce Type: new Abstract: We approach a cognitive simulation perspective on episodic and semantic memory in multiple-choice question answering by incorporating text from individu

safetyarxiv-cs-cl

From Version Conflicts to Decision Conflicts: Selective Revalidation for Long-Running AI Agents

arXiv:2609.08015v1 Announce Type: new Abstract: Long-running AI agents may read state, reason, wait for tools or human approval, and perform an external action much later. The state that justified the

Tutorials

HoarePrompt: Structural Reasoning About Program Correctness in Natural Language

arXiv:2503.19599v3 Announce Type: replace-cross Abstract: While software requirements are often expressed in natural language, verifying the correctness of a program against such requirements is a har

tutorialsarxiv-cs-ai

It is Not Yet Another Tool: Creating and Deploying an Agentic AI Companion in a Security Operations Center

arXiv:2609.06250v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) process large amounts of tickets, most of which are low-interest events not worthy of further investigation. The re

PocketAgents: A Manifest-Driven Library of Autonomous Defense Agents

arXiv:2605.21694v2 Announce Type: replace-cross Abstract: Connecting large language models (LLMs) to defensive enforcement requires more than asking a model whether an attack is happening. A defender

Quantization Amplifies Determinism, Not Bias: Scale-Dependent Behavioral Effects of Serving-Time Weight Compression

arXiv:2609.07901v1 Announce Type: new Abstract: Weight quantization largely determines the economics of serving open-weight LLMs. Its costs are usually assessed with capability benchmarks, on which 4-

Quantum Feature Engineering for Credit Default Prediction: When and Why IQP Circuits Help Linear Classifiers

arXiv:2609.10505v1 Announce Type: new Abstract: Credit default prediction is a tabular classification problem in which modest gains in F1 translate directly into reduced financial exposure. We ask whe

researcharxiv-cs-lg

Revoked but Still Authoritative: An Empirical Study of Revocation Enforcement in Agent-Memory Systems

arXiv:2609.08258v1 Announce Type: new Abstract: Long-running language-model agents depend on persistent memory. Many agent-memory systems preserve history through soft revocation: a contradicted fact

Silent Revision: Measuring Undisclosed Change in the Safety Frameworks of Frontier AI Developers

arXiv:2609.08789v1 Announce Type: cross Abstract: Frontier AI developers publish safety frameworks that commit them to evidencing whether their models are dangerous. The European Union and California

Local Ai

Skynet: Workflow-Level Anomaly Detection for Agentic AI via Semantic and Structural Modeling

arXiv:2609.06835v1 Announce Type: cross Abstract: Agentic AI systems execute complex tasks through long-horizon workflows of planning, tool use, and multi-agent coordination. Task failures in these sy

local-aiarxiv-cs-ai

Applications

Solving versus Verifying: Catching Contradictions in Tax Reasoning Systems

arXiv:2609.05928v1 Announce Type: cross Abstract: Large language models now compute correct tax liabilities on over 90% of well-formed cases in statutory benchmarks, which makes them candidates for th

applicationsarxiv-cs-ai

Towards Automatic Evolution Tree Generation from Citation Graphs

arXiv:2609.09561v1 Announce Type: new Abstract: Surveys remain the primary way researchers grasp the lineage of methods within an AI subfield, but they scale poorly against the current rate of publica

UniRRM: Unified Reasoning Reward Models Across Languages and Evaluation Paradigms

arXiv:2609.05910v1 Announce Type: cross Abstract: Reinforcement learning (RL) excels on tasks with verifiable rewards, but in open-ended tasks, the reliability of reward models remains a key challenge

VST: Verifiable Structured Transport for Auditable Agent-to-Agent Alpha Discovery

arXiv:2609.07065v1 Announce Type: new Abstract: Agent-to-agent (A2A) alpha discovery is slowed by repeated feedback cycles between mining and evaluation agents, whose hand-offs, in contemporary LLM mu

When Do Large Language Models Exhibit Unsolicited Deception?

arXiv:2504.00285v2 Announce Type: replace Abstract: Large Language Models (LLMs) are effective at deceiving when prompted to do so. Models that demonstrate better performance on reasoning tasks are al

agentsarxiv-cs-cl

Who Are They to Each Other? Multi-Agent Reasoning for Speaker Relationship Inference

arXiv:2609.09628v1 Announce Type: cross Abstract: Inferring speaker relationships from spoken conversations is an important step towards socially aware speech understanding. However, this task remains

agentsarxiv-cs-cl

Who Maintains Agent Skills? A Longitudinal Study of Human-Governed, AI-Assisted Skill Maintenance

arXiv:2609.05677v1 Announce Type: cross Abstract: Lifelong LLM agents increasingly rely on external skill artifacts as one element for preserving and reusing capabilities over time. These skills (usua

A Closed-Form Estimator and Diagnostic Battery for Anchor-Judge Error Correlation, Under a Single-Common-Factor Model

arXiv:2609.08826v1 Announce Type: cross Abstract: When an external reference set (an anchor) is used to decompose an LLM-judge panel's error into a quality signal and a shared common-mode error, stand

safetyarxiv-cs-lg

CrossModalQA: A Cross-modal and Multi-hop Benchmark for Multimodal Retrieval-augmented Generation

model-releasesarxiv-cs-cv

arXiv:2609.05518v1 Announce Type: new Abstract: Despite the strong capabilities of multimodal large language models (MLLMs), their parametric knowledge remains incomplete and difficult to update, moti

From Narrative to Auditable Forecasts: A Structured Scaffold for Agentic Forecasting

arXiv:2609.05905v1 Announce Type: cross Abstract: LLM agents are increasingly used for live forecasting, where they retrieve up-to-date information and produce estimates for unresolved future events.

agentsarxiv-cs-lg

MOAE: Multi-Objective Agent Evolution with Pareto-Preserving Search

model-releasesarxiv-cs-lg

arXiv:2609.05992v1 Announce Type: cross Abstract: As LLM-based agents continue to advance, their evaluation has become increasingly multifaceted: a capable agent must not only achieve high task comple

RePro: Training Language Models to Faithfully Recycle the Web for Pretraining

arXiv:2510.10681v2 Announce Type: replace-cross Abstract: High-quality data is a cornerstone of large language model (LLM) pretraining, yet its growth has not kept pace with the needs of frontier mode

researcharxiv-cs-lg

Rethinking the Evaluation of Efficiency Methods for Multi-Agent Systems

model-releasesarxiv-cs-lg

arXiv:2609.05933v1 Announce Type: new Abstract: Efficiency is increasingly important for Large Language Model (LLM)-based multi-agent systems (MAS), as larger models and more agents introduce substant

au^au-Bench: An Environment for End-To-End, Realistic Agent Construction

arXiv:2609.04611v1 Announce Type: new Abstract: LLM agents are rapidly becoming production software, deployed to handle customer service, adjudicate disputes, and operate internal systems. Notably, th

Can Activation Steering Capture Multidimensional Authorship Style?

arXiv:2609.04792v1 Announce Type: cross Abstract: Activation steering has shown promise for controlling LLM generation along well-defined attributes, but it remains unclear whether it can handle the m

CoSkill: Joint Reinforcement Learning of Reasoning and Meta-Skill Agents for Hierarchical Skill Evolution

arXiv:2609.04865v1 Announce Type: new Abstract: Skill libraries improve the sample efficiency of agentic reinforcement learning (RL) by enabling large language model (LLM) agents to reuse procedural k

EVOHARNESSBENCH: Can Your Agents Keep Pace with an Evolving Harness?

arXiv:2609.04280v1 Announce Type: cross Abstract: Modern LLM-based agents operate through a harness of tools, reusable skills, and specialist agents that shapes what they observe and what they can do.

How to Speculate about Uncertainty in Agentic Coding? A Draft-Model Gate Method

model-releasesarxiv-cs-lg

arXiv:2609.05274v1 Announce Type: new Abstract: LLM agents deployed for software engineering fail expensively: they act confidently wrong, and bad actions are recognized only after costly execution an

Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

arXiv:2609.05314v1 Announce Type: new Abstract: Building automation systems generate rich sensor data yet remain insight-poor because heterogeneous point naming, missing metadata, and fragmented docum

Large Language Models with At Most One Spike per Neuron

arXiv:2609.05151v1 Announce Type: cross Abstract: Leveraging their inherent sparse event-driven computation, spiking neural networks (SNNs) offer a promising path toward energy-efficient large languag

researcharxiv-cs-cl

Leveraging Low-Level Symbolic Competences for Unsupervised Grounding in Hallucination Detection

arXiv:2609.05025v1 Announce Type: cross Abstract: Hallucination-where a language model generates outputs that are factually incorrect or unsupported by the source-is a major challenge for both prompte

Multi-Step Tool-Calling over Korean Open Public APIs: A Benchmark and a Data-Synthesis Recipe

arXiv:2609.05395v1 Announce Type: new Abstract: Data-sovereignty regulations increasingly require public institutions to deploy open-source, on-premise LLM agents that chain multiple tool-calls across

Persistent Teacher Anchoring for Tool-Using Agents

arXiv:2609.04773v1 Announce Type: cross Abstract: Distillation is common in LLM post-training, where on-policy knowledge distillation (OPKD) uses student-generated trajectories to prepare the student

Towards Understanding Pause Token Fine-Tuning Dynamics: A Mode Retention Perspective

arXiv:2609.04489v1 Announce Type: cross Abstract: Pause-token methods improve LLM reasoning by inserting special tokens into sequences. Prior work explains these gains through computational expressivi

Uncertainty Signals for Network Intent Translation: Risk Ranking and Ambiguity Localization

arXiv:2609.04486v1 Announce Type: cross Abstract: Intent-based networking realization starts by translating high-level intents into low-level network configurations. Recent approaches have shifted tow

Adapting to Evolving Requirements: Agentic AI for Retail Supply Chain Operations

arXiv:2609.03860v1 Announce Type: new Abstract: Retail supply chain operations rely on coupled decision modules that must adapt as requirements evolve. LLMs offer a natural-language interface for this

Beyond BLEU: A Case for Redefining Sign Language Translation Benchmarks

arXiv:2609.03734v1 Announce Type: cross Abstract: BLEU-4 is the standard metric for evaluating sign language translation (SLT), but spoken-language metrics may not adequately reflect sign language pro

IndicSafeEval: Safety Robustness of Large Language Models under Multilingual Persuasive Jailbreak Attacks

arXiv:2609.03781v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in multilingual settings, yet their safety is still evaluated primarily in English. This limits our

Learning What Not to Forget: Long-Horizon Agent Memory from a Few Kilobytes of Learning

arXiv:2606.20954v2 Announce Type: replace-cross Abstract: Long-running language-model systems accumulate interaction history that outgrows the context window, so they must continually evict. When an e

Margins, Not Windows: Training-Free Per-Step Lossy Speculative Decoding

arXiv:2609.02897v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting candidate tokens and verifying them in parallel. Tree-attention drafters such as EAGLE-3 are

SWIM: Student Writing Simulation via Proficiency-Conditioned Generation

arXiv:2609.03215v1 Announce Type: new Abstract: Writing proficiency manifests in how students develop content, organize ideas, choose words, and use language. Despite growing interest in LLM-based stu

safetyarxiv-cs-cl

The Civilization Framework: Sovereign-Anchored Communication Between Personal Multi-Agent Systems

arXiv:2609.03425v1 Announce Type: cross Abstract: Humans are the transport layer between AI systems, losing context at every hop. We present the Civilization Framework, whose addressable party is the

What Do CAE Simulation Agents Really Need Beyond a Generic Harness?

arXiv:2609.03718v1 Announce Type: cross Abstract: Computer-aided engineering (CAE) simulation is among the largest and most demanding areas of engineering, where setting up a solver such as OpenFOAM,

agentsarxiv-cs-cl

What Else Needs Fixing? Exploring Cost-Effective Test-Time Compute for Revision Propagation in Artifacts Generated Through Conversation

arXiv:2609.03254v1 Announce Type: new Abstract: Large Language Models (LLMs) often help users generate artifacts through iterative cycles of generation and revision in conversation. A challenge here i