Search: “reasoning”

What Should an Agent Forget? Separating What Is Stored from What Is Used

arXiv:2609.10263v1 Announce Type: new Abstract: Persistent language agents need stored experience to remain available across time, while each answer requires evidence suited to a particular question.

11 Sept 2026

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When Noise Fabricates Bias: The Fragility of LLM-as-a-Judge Bias Measurement under Noisy Text

DGX agent

arXiv:2609.11067v1 Announce Type: new Abstract: Large language models are increasingly used as judges to measure social bias in text, yet the passages they judge are often noisy, containing typos, inf

safetyarxiv-cs-cl

11 Sept 2026

XAI-Arena: Can LLMs Assess the Quality of XAI Explanations?

arXiv:2609.09428v1 Announce Type: new Abstract: Evaluating the quality of explanations produced by explainable AI (XAI) methods remains challenging because existing approaches often rely on subjective

11 Sept 2026

Xiaomi-CocktailASR-1 Technical Report

arXiv:2609.11274v1 Announce Type: cross Abstract: Recently, large language model (LLM) based ASR models have achieved significant progress, yet they generally lack support for multi-speaker scenarios,

applicationsarxiv-cs-cl

11 Sept 2026

AgentIdeaBench: Benchmarking Scientific Ideation in the Agent Era

arXiv:2609.07611v1 Announce Type: new Abstract: Scientific ideation is the capacity to formulate novel and testable hypotheses from scientific evidence, and autonomous AI scientists depend on it. Exis

Artificial Intelligence Literacy and Sustainable Development: An Ethical Governance and Development Goals Framework

arXiv:2609.10489v1 Announce Type: new Abstract: AI literacy provides foundational competencies that support ethical, transparent, and sustainable technological development, although higher-order capab

applicationsarxiv-cs-cv

Attribution in Scientific Literature: New Benchmark and Methods

arXiv:2405.02228v4 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly generate citation-backed responses, yet citation hallucination remains a major challenge for trustwo

Benchmarking Hybrid Deep Research Across Database Querying and Web Search

model-releasesarxiv-cs-cl

arXiv:2609.09410v1 Announce Type: new Abstract: While autonomous agents have made significant strides in 'deep research' by iteratively navigating the open web to synthesize information, real-world pr

Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering

arXiv:2505.13520v2 Announce Type: replace-cross Abstract: Textbook question answering (TQA) is a complex task, requiring the interpretation of complex multimodal context. Although recent advances have

Beyond Top-k Skill Retrieval: Diversity-Aware Skill Routing for LLM Agents

arXiv:2609.05824v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on external skills, but routing user requests over large skill registries is difficult because many

BIO-MEMART: Biometric-Aware KV Cache Memory for Multi-User LLM Agents

arXiv:2609.08566v1 Announce Type: new Abstract: KV cache is evolving from a serving optimization into an external memory substrate for long-term LLM agents. In a shared multi-user deployment, however,

Can We Trust Video Hallucination Detectors? VidHalLoc for Evaluating the Evaluators

model-releasesarxiv-cs-cv

arXiv:2609.09895v1 Announce Type: new Abstract: Video-language models and video agents can produce hallucinations that conflict with spatiotemporal evidence. Existing benchmarks mainly evaluate model

CausalVerify: An Execution-Grounded Benchmark for LLM Causal Inference Workflows

arXiv:2609.07944v1 Announce Type: new Abstract: Existing causal-inference benchmarks for LLMs mostly score method descriptions or whether generated code runs, not whether the executed workflow recover

CircuTutor: Transforming Static Circuit Problems into Intelligent and Dynamic Tutoring

arXiv:2609.08254v1 Announce Type: new Abstract: Learning direct current circuit concepts requires learners to connect invisible physical quantities, such as current, voltage, resistance, and power, wi

applicationsarxiv-cs-ai

Tutorials

Cross-Species Animal Re-Identification with Semantic Consistency Learning

arXiv:2609.09705v1 Announce Type: new Abstract: Generalizable animal Re-Identification (ReID) aims to recognize individual animals across species with diverse morphologies and ecological contexts. Unl

tutorialsarxiv-cs-cv

Data-Driven Risk Fields for Safer End-to-End Autonomous Driving

arXiv:2609.10377v1 Announce Type: cross Abstract: Safety is a fundamental requirement for autonomous driving, yet existing end-to-end driving models still lack explicit risk-aware learning capacities.

safetyarxiv-cs-cv

Deterministic Prompting for Speaker-Stable Low-Resource Greek TTS

arXiv:2609.10022v1 Announce Type: cross Abstract: Modern TTS systems approach human quality for high-resource languages but degrade when clean speech data is scarce. Modern Greek exemplifies this, lac

safetyarxiv-cs-cl

Evaluating and Improving Evidence-Grounded Fact-Checking in LLMs via Multi-Round Evidence Ablation

arXiv:2609.08943v1 Announce Type: cross Abstract: Automatic fact-checking systems assess the veracity of claims given evidence from relevant documents. Large Language Models (LLMs) have demonstrated s

Explainable Token-level Noise Filtering for LLM Fine-tuning Datasets

arXiv:2602.14536v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have seen remarkable advancements, achieving state-of-the-art results in diverse applications. Fine-tuning, an im

Feyospace-v1: How the Cyber Mercury Seven Trained Frontier Cyber Models

arXiv:2609.08418v1 Announce Type: new Abstract: Training capable cyber agents is often treated primarily as a problem of model scale, yet open-weight post-training is constrained more directly by the

FreqBLiMP: Frequency-Controlled Minimal Pairs Reveal Robustness and Fragility of LLMs Under Lexical Rarity

arXiv:2609.07153v1 Announce Type: cross Abstract: Minimal-pair benchmarks such as BLiMP evaluate linguistic knowledge by testing whether language models (LMs) prefer acceptable sentences over minimall

From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Mining

arXiv:2609.07984v1 Announce Type: new Abstract: Process mining has long turned event logs into process knowledge: discovered models, conformance evidence, bottleneck diagnoses, and runtime predictions

Human-like moral judgments conceal divergent motive attributions in large language models

arXiv:2609.07353v1 Announce Type: new Abstract: Large language models (LLMs) are used to simulate human participants in psychological research. We asked whether LLMs that reproduce human evaluations o

Improving Cross-Lingual Token Representations by Adding a Pinch of SALT

arXiv:2609.09953v1 Announce Type: new Abstract: Cross-lingual sentence encoders enable scalable transfer across hundreds of languages, powering applications such as translation mining and zero-shot le

safetyarxiv-cs-cl

Improving Proficiency and Efficiency of Android GUI Agents via Self-Generating Tool Actions

arXiv:2609.06792v1 Announce Type: new Abstract: Android agents using a hybrid action space that combines GUI actions and tool actions (e.g., accessing application data via APIs) remain largely underex

Inferring the Unspoken: Aligning Embodied Agents with Implicit Preferences

arXiv:2502.00858v4 Announce Type: replace Abstract: Natural-language instructions rarely specify every detail required for embodied action. An agent asked to ``prepare an apple,'' for example, must st

Integrating Unimodal and Vision-Language Representations in Latent Space for Multi-Label Chest X-Ray Classification

arXiv:2609.09185v1 Announce Type: new Abstract: Multi-label chest X-ray classification has attracted considerable attention in recent years, with the effective use of visual representations and clinic

applicationsarxiv-cs-cv

Kernel-Managed Shared Memory for System-Wide Personalization

model-releasesarxiv-cs-lg

arXiv:2609.10144v1 Announce Type: cross Abstract: AI systems become more useful when they can adapt to the people using them, but in multi-agent systems, useful context learned by one agent often rema

Measuring LLM Sycophancy under Sustained Multi-Turn Pressure

arXiv:2609.09090v1 Announce Type: cross Abstract: Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy. Existing evaluations t

MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

model-releasesarxiv-cs-cl

arXiv:2609.10016v1 Announce Type: cross Abstract: We introduce MetroLLM-Bench, a 955-case benchmark for testing language models as the policy layer of a transit kiosk. It covers six real metro systems

MotionBlind: Probing the Illusion of Motion Understanding in Video-LLMs

model-releasesarxiv-cs-cv

arXiv:2609.09528v1 Announce Type: new Abstract: Video large language models (Video-LLMs) are increasingly used as the perceptual front end of world models, a role that assumes they can read motion: ho

Muse-glimmer-30b really punches above its weight(s) for creative writing

model-releasesr-localllama

After noticing that it is ranked among MUCH larger frontier models in the EQ-Bench Creative Writing benchmark and the Hemingway-bench, I decided to give it a try and was very impressed. I didn't do ve

On-Policy Distillation for Vision-Language Model Adaptation, an Effective Paradigm on Low-Quality Multimodal Data

arXiv:2609.10321v1 Announce Type: new Abstract: Knowledge distillation offers an efficient route to transfer a task-adapted vision-language teacher to a compact student. The training target in current

safetyarxiv-cs-cl

Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnostics

arXiv:2609.09070v1 Announce Type: cross Abstract: Clinical AI evaluation should encompass diagnosis and management after adaptive information gathering. We compared Doctorina, eight physicians and fou

ProbPlug: A Plugin Uncertainty Network for Reliable Confidence in LLM Binary Classification

arXiv:2609.10122v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance across a broad range of classification settings, yet the reliability of their predictions

researcharxiv-cs-cl

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-

Tutorials

RAU: Reference-based Anatomical Understanding with Vision Language Models

arXiv:2509.22404v2 Announce Type: replace Abstract: Anatomical understanding, which is the ability to identify, localize, or segment anatomical structures, is critical in medical image analysis; howev

tutorialsarxiv-cs-cv

Tutorials

SCAFFOLD: Self-Improving Web Agents via Recursive Parametric Skill Abstraction

arXiv:2609.05511v1 Announce Type: new Abstract: Web agents need to navigate visually rich, long-horizon interfaces that change across sites, yet most previous agents still learn each task in isolation

tutorialsarxiv-cs-ai

SCIRIGOR:Evaluating Open-Ended Scientific Analysis Beyond Final Scores

arXiv:2609.06192v1 Announce Type: new Abstract: Scientific coding agents produce interdependent code, results, figures, and claims, yet evaluating final outputs alone does not establish whether their

SocialRL: Refining LLMs' Social Intelligence through Multi-turn Reinforcement Learning and Reward Design

arXiv:2609.09764v1 Announce Type: new Abstract: Social intelligence enables agents to read social context, infer intent, and adapt over sustained dialogue. As language models become autonomous collabo

agentsarxiv-cs-cl

SRD-GUARD: A Defense Framework of LLMs via Semantic Rewriting and Joint Multi-Model Scoring for Latent Intent Exposure

arXiv:2609.06540v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in safety-critical applications, yet jailbreak attacks can conceal harmful intent through role-

SRPO: Setwise Relative Policy Optimization for Multi-Agent LLMs

arXiv:2609.08452v1 Announce Type: new Abstract: Multi-agent large language models solve complex tasks by coordinating several policies in a shared environment. However, existing reinforcement learning

Storage-Scalable Progressive Semantic Communication via Knowledge-Base Reuse

arXiv:2609.10112v1 Announce Type: new Abstract: Existing knowledge-base-assisted semantic communication schemes commonly adopt either single knowledge-base quantization (SKBQ) or multi-knowledge-base

researcharxiv-cs-lg

The Answer Path and the Grounding Instruction in LLM Question Answering over Knowledge Graphs

arXiv:2609.10237v1 Announce Type: new Abstract: A graph retrieval-augmented generation pipeline chooses which triples to put in the prompt, a syntax to write them in, an order to write them in, and a

researcharxiv-cs-cl

The Internal Anatomy of Strategic Choice in Large Language Models

arXiv:2609.07478v1 Announce Type: new Abstract: Large language models act as strategic agents and models of human choice, yet choosing like a strategic agent does not mean computing like one. We recor

The Profit Alignment Problem: How Profit Mandates Induce Alignment Failures in LLMs

arXiv:2609.07731v1 Announce Type: new Abstract: We show that ordinary business language --- 'maximize profitability' --- induces profit-oriented ambiguity resolution: LLMs systematically dismiss ambig

We're Cooked! - Probing LLM Political Alignment Via Conflict-Framed Recipe Translation

arXiv:2609.07568v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed for translation tasks, yet their implicit political positioning in such contexts remains unders

What Does a System Modify When It Modifies Itself?

arXiv:2603.27611v2 Announce Type: replace Abstract: When a cognitive system modifies its own functioning, what exactly does it modify: a low-level rule, a control rule, or the criterion that evaluates