Search: “llm”

Jailbreaking Text-to-Image Models Through Cracks: Navigating Heterogeneous Safety Filters via Multi-Agent Debate

arXiv:2609.01168v1 Announce Type: new Abstract: Text-to-image (T2I) models remain vulnerable to jailbreak attacks that elicit Not-Safe-For-Work (NSFW) content, despite increasingly being guarded by he

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Learning to Remember: End-to-End Training of Memory Agents for Long-Context Reasoning

DGX agent

arXiv:2602.18493v2 Announce Type: replace-cross Abstract: Long-context LLMs and Retrieval-Augmented Generation defer state tracking and evidence consolidation to query time, which is brittle when fact

model-releasesarxiv-cs-ai

2 Sept 2026

Mechanism Design for Alignment and Control

arXiv:2609.01595v1 Announce Type: cross Abstract: We develop a framework for mechanism design with AI agents whose alignment (preferences) and capabilities (feasible actions and information) are unkno

Applications

Medical Causal Hypothesis Verification with Large Language Models

arXiv:2609.00063v1 Announce Type: cross Abstract: The growing use of large language models (LLMs) for search and information retrieval underscores the need to evaluate their reliability in high-stakes

applicationsarxiv-cs-ai

MemoryWalker: Stop Training Agents on Contexts They Never Saw

arXiv:2609.00865v1 Announce Type: cross Abstract: Production agent harnesses such as Claude Code and Qwen-Agent compress context during rollout, but training under compression creates a conditioning p

MiNER: Fine-Tuned Biomedical Natural Language Processing for Malaria Disease Entity Recognition in Clinical Texts

arXiv:2609.00073v1 Announce Type: new Abstract: Malaria remains a significant global health burden, necessitating continuous research efforts to understand its complex molecular mechanisms, epidemiolo

MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery

arXiv:2603.03517v2 Announce Type: replace-cross Abstract: General-purpose large language models (LLMs) that rely on in-context learning do not reliably deliver the scientific understanding and perform

MUGEN: Generating Unlearnable Graph Examples for Multiple Learning Tasks

arXiv:2609.00696v1 Announce Type: new Abstract: Graph data across diverse domains can expose valuable relational information to unauthorized representation learning, creating a pressing need for prote

researcharxiv-cs-lg

MutMem-V2: Cryptographically Authorized Mutation in Persistent Agent Memory Portable Verification and Reproducible Evidence

arXiv:2609.01235v1 Announce Type: cross Abstract: MutMem V1 introduced retention-preserving, cryptographically authorized mutation for persistent agent memory but did not provide a complete portable v

OCGQuant: Outlier-Companion Grouping for NVFP4 Quantization

arXiv:2609.00066v1 Announce Type: cross Abstract: NVFP4 is an efficient microscaling format for low-bit inference, but activation outliers can still degrade quantization accuracy within NVFP4 blocks.

On Synthesis of Metric Interval Temporal Logics

arXiv:2609.01032v1 Announce Type: cross Abstract: Automated mining of formal specifications is vital for verifying real-time systems. However, existing passive learning approaches remain restricted to

OpenAgentFlow: Enabling System-Wide Safety Boundaries for Heterogeneous AI Agent Fleets

arXiv:2609.00015v1 Announce Type: new Abstract: AI agents powered by large language models are evolving from isolated assistants into heterogeneous systems in which multiple agents, planners, controll

ParaStudent: Closing the Sim2Real Gap in User Simulators for AI Tutor Evaluation

arXiv:2507.12674v3 Announce Type: replace-cross Abstract: Evaluating Artificial Intelligence (AI) tutor feedback before deployment requires anticipating student engagement, typically assessed through

Parsing the Stream: A Live Trace Model for Long-Horizon Agents and Their Observers

arXiv:2609.01466v1 Announce Type: new Abstract: A long-horizon agent's trace outgrows both of its consumers: the human observer monitoring the run, and the agent itself, whose bounded context the trac

Prompt-Robust Language Models: Which Training Strategies Work?

arXiv:2609.01217v1 Announce Type: new Abstract: Despite their strong performance, large language models remain highly sensitive to prompt formulation. Prior work addresses this through refined data co

RadMatch: Auditable Radiology Report Evaluation via Finding-Level Matching

arXiv:2609.01470v1 Announce Type: new Abstract: As AI systems are increasingly used to draft radiology reports, reliably evaluating their clinical quality remains a critical challenge. Large language

safetyarxiv-cs-cv

RecalibrateGPT: AI Fatigue Resilient Conversational Interfaces

arXiv:2609.00506v1 Announce Type: cross Abstract: Large language models are powerful, but their interfaces often devolve into a type rightarrow read rightarrow retype loop, creating conversational AI

Recursive Criticality of AI Self-Improvement

arXiv:2609.00137v1 Announce Type: new Abstract: AI is increasingly used in the R&D process that produces future AI systems. We study the conditions under which this feedback becomes self-amplifying. O

Replacing Training with Memory: Listwise Selection for Text-to-SQL

arXiv:2609.00834v1 Announce Type: cross Abstract: Modern Text-to-SQL systems often follow generate-execute-select pipelines, generating multiple candidate queries then selecting the best one. Listwise

REVISE: Validity-Guided Recovery for Online Revisions in Agent Workflows

arXiv:2609.00643v1 Announce Type: new Abstract: Agent revisions expose a fundamental correctness--efficiency trade-off during concurrent execution. Discarding ongoing work preserves latest-version cor

agentsarxiv-cs-ai

Right Frame, Wrong Rule: Cultural Cues Expose the Financial Knowledge Gap They Were Meant to Close

arXiv:2609.00999v1 Announce Type: cross Abstract: When a question has valid answers under different normative frameworks, a language model must decide which framework to use and whether it can answer

Runtime-Independent Persistent Agents: Preserving Identity, Memory, and Code Across Models, Harnesses, and Servers

arXiv:2609.00546v1 Announce Type: cross Abstract: Agent systems are commonly described by the model and harness that currently produce their behavior. That boundary is useful for one execution but und

agentsarxiv-cs-ai

Safin-1: Safety from Within through Memory-Native State Evolution

arXiv:2609.00092v1 Announce Type: new Abstract: Long-horizon complex tasks require foundation models to accumulate information, maintain internal states, and adapt over extended interactions. Safety s

safetyarxiv-cs-lg

Slow to See, Slow to Suppress: Understanding the Effects of Modality in Context-Memory Conflicts

arXiv:2609.00293v1 Announce Type: new Abstract: We investigate how vision-language models (VLMs) handle context-memory conflicts; that is, situations in which the model is given information in context

safetyarxiv-cs-cl

SpokenUS: A Spoken User Simulator for Task-Oriented Dialogue

arXiv:2603.16783v2 Announce Type: replace Abstract: Robust voice agents require exposure to the full diversity of how people interact through speech. However, obtaining enough spoken interactions is p

researcharxiv-cs-cl

StateSwap: Probing Support-Elimination Hidden States in Multiple-Choice Questions

arXiv:2609.01081v1 Announce Type: cross Abstract: Large language models often answer the same multiple-choice question inconsistently when it is posed under support-oriented and elimination-oriented f

StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?

arXiv:2609.00787v1 Announce Type: new Abstract: Humans need to study only a handful of well-written textbooks to master a discipline and attempt its hardest problems. We argue that an ideal self-evolu

Task-Specific Prompt with Global Context for Multi-Task Graph Pre-Training

arXiv:2609.00047v1 Announce Type: cross Abstract: Graph prompt learning is an effective paradigm to adapt pre-trained graph models to downstream tasks in low-resource scenarios. However, existing mult

Topic Matching in the Wild: Benchmark and Lessons from Real-World ASR Transcripts

arXiv:2609.00330v1 Announce Type: cross Abstract: In contact centers, real-time agent-assist tools determine, for each of many predefined topics, whether a live customer utterance is relevant and disp

Verifiable Disaster Storylines and Causal Knowledge Graphs: A Citation-Grounded Pipeline from Heterogeneous Humanitarian Sources

arXiv:2609.00858v1 Announce Type: new Abstract: Effective humanitarian response depends on the rapid synthesis of heterogeneous, high-volume information sources - a task that routinely exceeds human a

Applications

Zero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AI

arXiv:2607.17883v2 Announce Type: replace-cross Abstract: Enterprises will not deploy AI agents they cannot trust, and the most-cited reason for distrust is hallucination: confident, fluent output tha

applicationsarxiv-cs-ai

A Cognitive Architecture for Shared Autonomy in AUV Operations

arXiv:2608.29347v1 Announce Type: new Abstract: Operators remain essential to Remotely Operated Vehicle (ROV) operation, yet often suffer from low situational awareness and high workload, both of whic

safetyarxiv-cs-ro

A Comprehensive Survey on Linguistic Steganography: Methods, Countermeasures, Evaluation, and Challenges

arXiv:2608.29077v1 Announce Type: cross Abstract: Linguistic steganography hides secret messages in natural language text. Large language models (LLMs) have reshaped the field, but a systematic accoun

researcharxiv-cs-cl

A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives

arXiv:2503.13415v2 Announce Type: replace-cross Abstract: With the rapid development of artificial intelligence, intelligent decision-making techniques have gradually surpassed human levels in various

agentsarxiv-cs-ai

A Model with No Head and Many Thoughts

arXiv:2608.31069v1 Announce Type: cross Abstract: Large language models decode by projecting hidden states through a large vocabulary head at every step. This operation is computationally costly and f

A research agent is only as good as the search layer behind it! I built a Deep Research Agent using LangChain Deep Agents with a search-firs…

A research agent is only as good as the search layer behind it! I built a Deep Research Agent using LangChain Deep Agents with a search-first architecture designed around grounded, source-backed resea

agentsharrison-chase--x

Agents in the Large: Perception-Centered Architecture for Persistent Agents

arXiv:2608.30478v1 Announce Type: new Abstract: Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling a

agentsarxiv-cs-cl

AIA^{2}: Attribute-Agnostic Imbalance Augmentation for Subgroup Robustness

arXiv:2608.30297v1 Announce Type: new Abstract: Attributes describing data content and context can induce diverse imbalance patterns that go beyond label imbalance alone. However, existing studies pri

researcharxiv-cs-cl

AlgoWorlds: Benchmarking Tool Use for Global Optimization in Algorithmic Worlds

arXiv:2608.29397v1 Announce Type: new Abstract: Tool-use benchmarks generally evaluate whether an agent completes a workflow using appropriate tools and valid arguments. However, feasibility alone is

ALTSTEER: Selective Safety Steering for Moving Beyond Hard Refusals to Constructive Alternatives

arXiv:2608.30197v1 Announce Type: new Abstract: Safety alignment is essential for deploying large language models, requiring systems to prevent harmful compliance while preserving helpfulness on benig

An Agentic Retrobiosynthesis Framework with Learned Frontier Selection

arXiv:2608.30702v1 Announce Type: cross Abstract: Large language models are increasingly used as agents for multistep retrosynthesis, raising the question of how much their search policy contributes i

An Open-Source, Event-Driven Pipeline for Cryptocurrency Market Data: Ingestion, Forecasting, and On-Chain Fraud Detection

arXiv:2608.29973v1 Announce Type: new Abstract: Cryptocurrency markets generate high-frequency, multi-source data that is expensive to work with unless a team already has commercial-grade streaming an

Autonomously Acquiring Robot Manipulation Skills with Language-Driven Quality-Diversity

arXiv:2608.30983v1 Announce Type: new Abstract: Quality-diversity (QD) algorithms have been gaining traction in robot learning, where diverse motion primitive libraries allow robots to adapt zero-shot

safetyarxiv-cs-ro

b10737

model-releasesllama-cpp-releases

qwen4exp: fix seq_cp, block position keying, mtmd input, cuda abort, add tests (#27941) qwen4exp: follow up fixes -kvu NaN collapse fix Assisted-by: Claude indexer cache ext.x/ext.y restore fix Assist

Banger paper from the Qwen team. If you evaluate agents on anything longer than a single session, this one is worth your time. (bookmark it)…

Banger paper from the Qwen team. If you evaluate agents on anything longer than a single session, this one is worth your time. (bookmark it) E-Commerce Bench runs an agent through a simulated 365-day

model-releasesdair-ai--x

Beyond Fluency: A Rubric-Based Benchmark for Evaluating Saudi Dialect and Cultural Competence in Large Language Models

arXiv:2608.29990v1 Announce Type: cross Abstract: Large language models are increasingly deployed in Arabic-speaking markets, yet standard benchmarks overwhelmingly reward Modern Standard Arabic (MSA)

Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence

arXiv:2606.15932v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have substantially advanced text-to-code generation, many real programming tasks specify intent through visual ar

agentsarxiv-cs-cl

Beyond Semantic Similarity: Reducing Unnecessary API Calls via Behavior-Aligned Retriever

arXiv:2508.14323v3 Announce Type: replace Abstract: Tool-augmented LLMs invoke external functions to extend their capabilities, but errors in the invocation decision, such as calling a tool when none