Search: “llm”

The Truth Stays in the Family: Enhancing Contextual Grounding via Inherited Truthful Heads in Model Lineages

arXiv:2606.15821v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have produced many specialized multimodal LLMs (MLLMs) that share common foundational LLMs, fo

12 Aug 2026

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UniMod: Enhancing Multi-Modal Medical Diagnosis through Cross-Modality and Within-Modality Alignment

DGX agent

arXiv:2608.10316v1 Announce Type: new Abstract: Multi-modal learning combining medical images and clinical text is promising for disease diagnosis. However, standard multi-modal training leads to shor

safetyarxiv-cs-cv

12 Aug 2026

VibeLifeBench: Can Your Life Agent Be Proactive and Persistent in a Living World?

arXiv:2608.10875v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly deployed as personal assistants. Existing evaluations, however, mostly use short, self-contained re

12 Aug 2026

Local Ai

Agentic AI-driven Immersive Simulation: A Knowledge-Aware Virtual Training Platform forHigh Dose Rate (HDR) Brachytherapy

arXiv:2608.08163v1 Announce Type: new Abstract: The convergence of the Metaverse and Large Language Model (LLM)-based AI agent is catalyzing a shift toward autonomous, immersive, and personalized peda

local-aiarxiv-cs-ai

Tutorials

Beyond the Node: Clade-level Selection for Efficient MCTS in Automatic Heuristic Design

arXiv:2602.00549v2 Announce Type: replace Abstract: While Monte Carlo Tree Search (MCTS) shows promise in Large Language Model (LLM) based Automatic Heuristic Design (AHD), it suffers from a critical

tutorialsarxiv-cs-lg

Business Truth, not SQL Accuracy: A Rule-Gated 7B Analytics Agent Outperforms a Direct-Prompted 32B Baseline

arXiv:2608.09254v1 Announce Type: new Abstract: LLM analytics agents are evaluated on SQL syntax accuracy, but production failures look different: questions with two valid business definitions, questi

DarwinX: Evolving Agent Harnesses Through Natural Selection

arXiv:2608.07545v1 Announce Type: cross Abstract: An LLM agent's capability depends not only on model weights but on its harness: prompts, tools, skills, and control flow. Self-improvement loops alrea

Different Feedback, Different Updates: Selective Self-Learning from User Interactions for Large Language Models

arXiv:2608.09109v1 Announce Type: new Abstract: User feedback offers natural supervision for persistent LLM improvement, but a single message may support multiple behavioral changes with different sco

researcharxiv-cs-ai

ForestBench: A Unified Graph Framework for Evaluating Multi-Agent Collaboration

arXiv:2608.08605v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on Large Language Models (LLMs) are proliferating rapidly, but their heterogeneous execution traces provide no common ba

Human-Level Text-to-SQL via Reinforcement Learning on Verified Data, Without Pipeline Engineering

arXiv:2603.20004v3 Announce Type: replace-cross Abstract: Translating natural language questions to SQL queries (Text-to-SQL) is a long-standing problem in database research. Recent efforts have focus

researcharxiv-cs-cl

Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning

arXiv:2608.09507v1 Announce Type: cross Abstract: Natural language user preferences provide an interpretable interface for LLM personalization. However, universal preference summaries often contain in

Mismatch Matters: On-Policy Distillation Beyond Token Agreement

arXiv:2608.09836v1 Announce Type: new Abstract: On-policy distillation (OPD) has emerged as a core component of modern LLM post-training pipelines, yet we reveal a failure mode: degenerate agreement,

Mitigating Gender Bias in English to Romanian Machine Translation

arXiv:2608.08606v1 Announce Type: cross Abstract: Machine translation (MT) systems often fail to correctly translate gender, especially when converting from a gender-neutral language like English to a

MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

arXiv:2603.28590v3 Announce Type: replace Abstract: Large language models (LLMs) can generate chains of thought (CoTs) that are not always causally responsible for their final outputs. When such a mis

Query-Only Backdoor Attacks on Self-Evolving Skills via Trajectory Poisoning

arXiv:2608.08303v1 Announce Type: new Abstract: Agentic skills improve large language model (LLM) agents by encoding reusable procedures for complex tasks. However, manually authored skills often adap

RAG-Based Auto-Configuration for Industrial Fieldbus Devices

arXiv:2608.08618v1 Announce Type: cross Abstract: Industrial device commissioning requires engineers to manually extract hundreds of protocol-specific parameters from heterogeneous PDF manuals and tra

ReMIND: Orchestrating Modular Large Language Models for Controllable Serendipity A REM-Inspired System Design for Emergent Creative Ideation

arXiv:2601.07121v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used not only for problem solving but also for creative ideation; however, generating ideas that

researcharxiv-cs-ai

RippleKV: Cross-Layer KV Cache Allocation via Perturbation Propagation

arXiv:2608.08684v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by KV cache memory, yet distributing a limited cache budget across layers remains challenging. Existing met

Safety Cost of Steering Vectors Is Separable and Reducible

arXiv:2608.08383v1 Announce Type: new Abstract: Steering vectors are a lightweight tool for controlling LLM behavior. However, emerging evidence shows that steering vectors can unintentionally comprom

safetyarxiv-cs-cl

SkillsMetric: Mapping the Detection Boundary of Static Analysis for Malicious Agent Skills

arXiv:2608.08468v1 Announce Type: cross Abstract: Agent Skills---structured packages of instructions and scripts that augment LLM-based agents---are rapidly proliferating, yet their security propertie

Tied Trit-Planes: Constraining PTQTP to a Uniform Nine-Level Quantizer, with a Persistent Folded Format for Disk-Streamed Mixture-of-Experts Serving

model-releasesarxiv-cs-cl

arXiv:2608.08910v1 Announce Type: new Abstract: PTQTP decomposes LLM weight matrices into two ternary (trit) planes with two free per-group scales. Tying the scales to a fixed ratio of three collapses

Toward Metacognitive One-Shot Indirect Prompt Injection: Strategy Abstraction Via Outcome-Conditioned Reflection

model-releasesarxiv-cs-cl

arXiv:2608.08795v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents are vulnerable to indirect prompt injection (IPI), in which malicious instructions embedded in external o

What Keeps Agent Skills from Being Reusable? Evidence from 138K SKILL.md Files

arXiv:2608.08453v1 Announce Type: new Abstract: Under the current standard, Agent Skills are SKILL.md files that combine instructions with supporting resources, enabling Large Language Model (LLM) age

Yesterday's Shield, Today's Spear: A Self-Evolving Safety Guardrail in Production

arXiv:2608.08471v1 Announce Type: new Abstract: Deployed LLM safety guardrails are predominantly static: trained once and frozen at release, while new jailbreak techniques and previously un-addressed

A Multi-Agent Framework for Automated Coarse-Grained Molecular Dynamics of Polymers

arXiv:2608.06694v1 Announce Type: new Abstract: Coarse-grained (CG) molecular dynamics extends polymer simulation beyond the scales accessible to all-atom (AA) methods, but bottom-up CG modeling is la

A Picture is Worth a Thousand Tokens: How Vision Language Models Cut AI Energy Costs While Improving Accuracy

arXiv:2608.07427v1 Announce Type: new Abstract: LLM inference accounts for over 90% of AI operational energy, scaling directly with input token count---a critical inefficiency for telecom network anal

Beyond Text Matching: Towards Reference-Free Evaluation for Human-Oriented Binary Reverse Engineering

arXiv:2608.07038v1 Announce Type: cross Abstract: Human-Oriented Binary Reverse Engineering (HOBRE) aims to transform decompiled pseudocode into a more human-friendly representation, thereby reducing

CHIME: A Case for Efficient Long-Context Attention-FC Disaggregated Inference with DIMM-PIM

arXiv:2504.17584v2 Announce Type: replace-cross Abstract: Attention-FC Disaggregated (AFD) LLM inference systems offload memory-bound Attention operations to memory-rich accelerators (e.g., CPUs, HBM-

safetyarxiv-cs-lg

CyberForge: Verified Vulnerability Injection at Repository Level for Cybersecurity Agent Training

arXiv:2608.06471v1 Announce Type: cross Abstract: Despite recent advances, frontier large language model (LLM) agents remain limited in discovering and patching complex vulnerabilities in real-world s

EMAS: Stabilizing Multi-Agent System Evolution through Evidence-Guided Revision

arXiv:2608.07196v1 Announce Type: new Abstract: Many methods for automated multi-agent system design optimize prompts and topologies during an initial design stage and then deploy the resulting system

Tutorials

LoRAScan: Detecting Backdoor Prompts in Low-Rank Adapters for Large Language Models via Down-Projection Activation Spikes

arXiv:2608.06795v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) enables efficient specialization and distribution of large language models through compact adapters. However, untrusted ada

tutorialsarxiv-cs-ai

Multi-Perspective Triad Interaction Graph Neural Network for Cognitive Distortion Detection

arXiv:2608.06785v1 Announce Type: new Abstract: Cognitive distortion detection is a key task in computational mental health, yet existing approaches often overlook the psychological structure of disto

safetyarxiv-cs-cl

Natural Language Processing Psychometrics

arXiv:2608.07316v1 Announce Type: cross Abstract: Natural Language Processing (NLP) models predicting mental health outcomes rarely specify what they measure: contextual knowledge, emotional content,

researcharxiv-cs-ai

Local Ai

Online Monitoring and Corrective Steering of Programming Agents

arXiv:2608.06701v1 Announce Type: cross Abstract: Fixing GitHub issues in large-scale projects is a long-horizon task, especially when a fix requires changes across multiple locations or the issue des

local-aiarxiv-cs-ai

PHASE-Tree: Modeling Character-State Evolution in Long-Horizon Role-Playing Dialogue

arXiv:2608.06975v1 Announce Type: cross Abstract: Long-horizon role-playing demands that characters remain recognizable as they evolve with the narrative. Yet existing work falls short on two fronts:

ResidencyRL: Reinforcement Learning in Simulated Clinical Environments

arXiv:2608.07418v1 Announce Type: new Abstract: In medical education, physicians convert academic knowledge into clinical expertise through residency: years of training across thousands of encounters,

Agentic Software Issue Resolution with Large Language Models: A Survey

arXiv:2512.22256v2 Announce Type: replace-cross Abstract: Software issue resolution aims to address real-world issues in software repositories based on natural language descriptions provided by users,

AI Playing Business Games: Benchmarking Large Language Models on Managerial Decision-Making in Dynamic Simulations

arXiv:2509.26331v2 Announce Type: replace Abstract: The rapid advancement of LLMs sparked significant interest in their potential to augment or automate managerial functions. One of the most recent tr

APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning

arXiv:2608.05499v1 Announce Type: cross Abstract: Modern deep neural networks achieve strong performance, but their scale makes them costly and slow, especially on resource-constrained edge devices. P

Causal Episodic Memory for Feedback-Driven Agent Repair

model-releasesarxiv-cs-cl

arXiv:2608.05906v1 Announce Type: new Abstract: LLM agents that repair failures often discard successful corrections, forcing later episodes to rediscover similar solutions. We study whether finalized

DASH: Decoupled Adaptive Surrogate - Acquisition Harness for Automated Bayesian Optimization

arXiv:2608.00641v2 Announce Type: replace Abstract: Bayesian optimization (BO) relies on a surrogate model and an acquisition function, yet the most suitable choices vary across tasks and optimization

Learning Globally Reusable Skills for Coding Agents

arXiv:2608.06153v1 Announce Type: cross Abstract: Automated skill evolution enables Large Language Model (LLM) agents to continuously improve without expensive retraining. However, existing approaches

LUNAR: Benchmarking Personalized Large Language Models on UNiversal User BehAvioR Logs

arXiv:2608.05246v1 Announce Type: new Abstract: Existing personalized LLM benchmarks primarily rely on textual personas or isolated behavioral signals, providing limited evaluation of cross-domain beh

On-Policy Delta Distillation for Multilingual Math Reasoning

arXiv:2608.05802v1 Announce Type: new Abstract: On-Policy Distillation (OPD) is emerging as a promising alternative to reinforcement learning for LLM post-training, yet its effectiveness in multilingu

safetyarxiv-cs-cl

Applications

Persona-Pruner: Sculpting Lightweight Models for Role-Playing

arXiv:2606.14695v2 Announce Type: replace-cross Abstract: Language Models (LMs) have shown remarkable potential as role-playing chatbots, delivering consistent, stylized interactions when given a spec

applicationsarxiv-cs-cl

Search2Skill: Skill Distillation Beyond Knowledge Boundaries Via Rubric-Based Reinforcement Learning

arXiv:2608.05245v1 Announce Type: new Abstract: Reusable skills, which encapsulate the procedural knowledge required to solve real-world professional tasks, offer LLM-based agents a path toward self-e

Tracing the Heart: An Evidence-Linked Pipeline for Heart-Failure Feature Engineering

arXiv:2608.06366v1 Announce Type: new Abstract: Electronic health record (EHR) feature engineering is a major bottleneck in clinical research and AI, accounting for 39-45% of data scientists' workload

TRAJDEBUG: Tracing Error Lifecycle to Identify Critical Failures in Long-Horizon Agent Trajectories

arXiv:2608.06346v1 Announce Type: new Abstract: LLM-based agentic systems have shown remarkable capabilities in complex domains, while suffering from cascading errors and difficulty in debugging. Crit