Search: “llm”

Uncertainty-Driven Replay Memory for Reinforcement Learning

arXiv:2608.29860v1 Announce Type: new Abstract: Uncertainty estimation provides promising capabilities for reinforcement learning (RL) agents. Notably, estimating uncertainty can reduce the training t

agentsarxiv-cs-lg

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Unveiling Language Routing Isolation in Multilingual MoE Models for Interpretable Subnetwork Adaptation

DGX agent

arXiv:2604.03592v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models exhibit striking performance disparities across languages, yet the internal mechanisms driving these gaps rema

researcharxiv-cs-ai

1 Sept 2026

VocalAffectBench: Evaluating Vocal Emotion Recognition in AI Audio Models

arXiv:2608.28932v1 Announce Type: new Abstract: Voice products increasingly need affective cues that are present in speech but absent from transcripts. We introduce VocalAffectBench, a public, test-on

What Does an Evaluation License? A Commit-Bound Census of Claim Replay in Inspect Evals

arXiv:2608.19269v4 Announce Type: replace-cross Abstract: Benchmarks can run without determining what their results license. We freeze a large evaluation collection and attempt to replay its historica

researcharxiv-cs-ai

What It Costs to Compose, Rebuild, and Correct Precomputed Memory

arXiv:2608.30647v1 Announce Type: new Abstract: Language models can answer from precomputed memory, a model's saved reading of a body of material, reused across requests instead of read again at each.

Local Ai

When Can We Work in Embedding Space? What Text Embeddings Preserve

arXiv:2608.31059v1 Announce Type: cross Abstract: When do text embeddings work as inputs to empirical analysis? Their use rests on an assumption: that we can trade text for its low-dimensional embeddi

local-aiarxiv-cs-cl

When History Is Multimodal: Rethinking Context Management for Long-Horizon Agents

arXiv:2608.29897v1 Announce Type: new Abstract: Long-horizon agents need a context manager to compress growing interaction histories into a bounded working context, via passive strategies or active st

You Know What I Mean: A Benchmark for Agentic Conversational Reference Grounding

arXiv:2608.29834v1 Announce Type: new Abstract: Collaborative conversations frequently contain references whose targets are indirect rather than named: resolving 'this looks like the fix discussed yes

A Unified Framework to Elicit Structured Feedback for Interpretable Multi-Trait Essay Scoring

arXiv:2608.28407v1 Announce Type: new Abstract: Multi-trait Automated Essay Scoring (AES) requires rubric-grounded reasoning across interdependent traits, rather than isolated score prediction. Existi

AIM: Anchor Identity Features, Then Match for Multimodal Large Language Model Unlearning

arXiv:2608.28312v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) can memorize identity-specific facts about people in their fine-tuning data, creating privacy risks when a pe

Amortizing intractable inference in diffusion models for vision, language, and control

arXiv:2405.20971v3 Announce Type: replace-cross Abstract: Diffusion models have emerged as effective distribution estimators in vision, language, and reinforcement learning, but their use as priors in

researcharxiv-cs-cv

An Enclosed Mode Is a Gauge Choice: Topology Relative to Reach in Certified Code World Models

arXiv:2608.28541v1 Announce Type: new Abstract: A code world model accepted by a sampling gate can be exactly right on everything the gate can see and arbitrarily wrong beyond it. We characterize what

Local Ai

ARC-CT: Anatomy-Routed Contrastive Vision-Language Learning for 3D Chest CT

arXiv:2608.28455v1 Announce Type: new Abstract: Contrastive vision-language learning uses paired chest CT volumes and radiology reports to learn abnormality classifiers without manually annotated labe

local-aiarxiv-cs-cv

Are These Modules Worth Their Cost? A Paradigm-Level Accuracy-Cost Analysis of In-context Learning Text-to-SQL

arXiv:2608.28432v1 Announce Type: new Abstract: Recent advances in in-context learning (ICL) text-to-SQL have substantially improved execution accuracy on public benchmarks by assembling increasingly

Beyond the Rabbit Hole: Mapping the Relational Harms of QAnon Radicalization

arXiv:2601.17658v2 Announce Type: replace Abstract: Large-scale computational research on conspiracy theories has focused exclusively on believers' online behavior, leaving the harm experienced by tho

ContextPilot: Teaching Agents for Proactive Context Management via Fine-grained RL

arXiv:2608.28476v1 Announce Type: new Abstract: Long-horizon agentic tasks require large language models (LLMs) to iteratively retrieve, integrate, and maintain dispersed information across multi-turn

agentsarxiv-cs-cl

CURA: Certified Runtime Alarms for Computer-Use Agents

arXiv:2608.27808v1 Announce Type: cross Abstract: Self-report is the cheapest oversight channel a deployer has, and on capable computer-use agents (CUAs) it fails precisely where oversight matters. On

researcharxiv-cs-cv

Embedding Models for Stance-Aware Argument Retrieval

arXiv:2608.28283v1 Announce Type: new Abstract: In computational argumentation, obtaining arguments that explicitly support or attack given claims is a critical precursor to downstream reasoning tasks

FedEHR-Agents: Federated Agentic Optimization for Automated EHR Modeling

arXiv:2608.27856v1 Announce Type: new Abstract: Recent advances in large language models are enabling autonomous clinical agents to perform increasingly complex electronic health record (EHR) modeling

FinExam-10K: When Retrieval Helps Financial Reasoning?

arXiv:2608.28155v1 Announce Type: new Abstract: Professional financial examinations require models to combine domain knowledge, calculation, and judgment, yet no benchmark covers the full CFA and FRM

First Make It Playable, Then Make It Good: Staged Interaction Learning for Small Dialogue-Game Agents

arXiv:2608.27672v1 Announce Type: new Abstract: We present Qwen-GuidePlay-2B, a 2B-parameter language model for dialogue-game interaction. We fine-tune Qwen3.5-2B using three steps: a) SFT on only suc

From Small Talk to Rapport: Exploring Robot Self-Disclosure in Collaborative Tasks

arXiv:2608.28154v1 Announce Type: new Abstract: People naturally chat while collaborating and share personal information (i.e., self-disclose) to build rapport and maintain social connections. As robo

researcharxiv-cs-ro

Fully Unleashing the Multimodal Attacker: Meta-Adaptive Jailbreaking of Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2608.27531v1 Announce Type: cross Abstract: The safety of large vision-language models is increasingly stress-tested by multimodal jailbreaks, yet existing attacks remain largely static at the m

HARTS: Efficient Agentic Reinforcement Learning for Hybrid-Attention Models over Arbitrary Rollout Trees

arXiv:2608.28158v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) often produces irregular rollout trees with shared histories. Training root-to-leaf trajectories independently recom

safetyarxiv-cs-lg

Linear Temporal Logic Translation via Human-Inspired Self-Constrained Reasoning for Robot Task Specification

arXiv:2608.28435v1 Announce Type: new Abstract: Many robotic tasks are temporally extended and demand precise specifications of subgoals, constraints, and their temporal ordering. Yet human operators

researcharxiv-cs-ro

Long Story Short: Story-level Video Understanding from 20K Short Films

arXiv:2406.10221v3 Announce Type: replace-cross Abstract: Recent developments in vision-language models have significantly advanced video understanding. Existing datasets and tasks, however, have nota

LUCID: An Agentic AI Framework on Digital-Twin in the Loop for QoS-Guaranteeing Robotic Control

arXiv:2608.28437v1 Announce Type: cross Abstract: Cloud robotics relies on the timely uplink of high-volume sensing streams, yet dynamic environments continually shift the feasible combinations of tra

agentsarxiv-cs-ro

Nested Byte-Level Vocabularies Are Cheap to Deploy and Expensive to Share: A Pre-Registered Negative Result

arXiv:2608.28151v1 Announce Type: new Abstract: A byte-level BPE tokenizer is an ordered list of merge rules, so applying only a prefix yields a vocabulary whose token identifiers are the first rows o

Plan Along the Way: Event-Triggered Foundation-Model Planning for TAMP Execution in Partially Observable Manipulation

arXiv:2608.28075v1 Announce Type: new Abstract: Manipulation in partially observable environments requires planning under incomplete scene information. In such settings, an initially valid plan may ex

researcharxiv-cs-ro

RealSWE: A Compositional Evaluation of Coding Agents under Realistic User Requests

arXiv:2608.27831v1 Announce Type: cross Abstract: Coding agents are now commonly evaluated on the SWE-bench family of benchmarks, whose tasks are built from curated GitHub issues--long, structured, an

Retrieving Relations, Detecting Fallacies: A RAG Approach to Political Debate Analysis

arXiv:2608.27471v1 Announce Type: cross Abstract: Fallacies are arguments that employ invalid reasoning, making their automatic detection critical in sensitive contexts such as high-stakes political d

Sledgehammer or Scalpel? A Fine-grained Adaptive Framework for Implicit Hate Speech

arXiv:2608.27462v1 Announce Type: new Abstract: Unlike explicit attacks with obvious profanity, implicit hate speech hides malice within seemingly compliant expressions through metaphors and contextua

Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning

arXiv:2608.28018v1 Announce Type: new Abstract: Knowledge-intensive reasoning requires Large Language Models (LLMs) to ground answers in provided evidence. When evidence is insufficient, it is desirab

When Can Conditional Flow Matching Replace Pointwise Negative Log-Likelihood?

arXiv:2608.28010v1 Announce Type: new Abstract: Flow matching enables likelihood-free training, yet alignment methods increasingly reuse conditional flow matching (CFM) losses as endpoint negative log

safetyarxiv-cs-lg

When Muon Meets Task Interference: A Spectral Perspective on Continual Learning and Model Merging

arXiv:2608.27518v1 Announce Type: new Abstract: Continual learning (CL) and model merging (MM) both aim to obtain a single model that performs well across multiple tasks, challenged respectively by ca

XHotpotQA: A Benchmark for Cross-Lingual Knowledge Composition in Multi-Hop Question Answering

arXiv:2608.27481v1 Announce Type: new Abstract: Knowledge-intensive multi-hop question answering requires systems to select evidence and compose dependent facts, yet multilingual benchmarks usually tr

AEScorer: An Agentic Evidence-Grounded Framework for Graded Factuality Verification

arXiv:2601.03605v2 Announce Type: replace Abstract: Despite the significant advancements of Large Language Models (LLMs), their factuality remains a critical challenge, creating a growing need for mor

AffectOmni: RL-Verifiable People-Centric Grounded Affective Reasoning for Social and Art-Related Scenes

arXiv:2608.26193v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) achieve strong performance on VQA and scene understanding, yet affective reasoning remains vulnerable to shortc

researcharxiv-cs-ai

Affix Cache for Diffusion Large Language Models

arXiv:2608.26140v1 Announce Type: new Abstract: Diffusion Large Language Models (DLLMs) enable non-autoregressive decoding and bidirectional context modeling, but efficient inference remains challengi

Agentic AI for operating scientific instruments for nanoscale characterization

arXiv:2608.26198v1 Announce Type: new Abstract: Operating a scientific instrument such as an atomic force microscope (AFM) requires continuous expert decision-making. A trained user defines the experi

agentsarxiv-cs-ai

AI Revealed Preferences

arXiv:2608.26178v1 Announce Type: new Abstract: There is growing interest in whether language models have stable preferences, for technical, safety, and philosophical reasons. We test 20 language mode

AraMS-28k: The Largest Publicly Released Line-Level Dataset of Historical Arabic Manuscripts with Margin and Insertion-Anchor Annotations

arXiv:2608.26921v1 Announce Type: cross Abstract: We introduce AraMS-28k, the largest publicly released line-level dataset of genuine historical Arabic manuscripts, comprising 14 books, 3,043 pages, a

Artificial Intelligence Models Can Predict and Collaboratively Modulate Human Memory Search

arXiv:2608.26152v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit unprecedented natural language generation and many text-based problem-solving capabilities. Indeed, in many langu

researcharxiv-cs-ai

Assessing mentalization in humans and large language models

arXiv:2608.26291v1 Announce Type: new Abstract: Mentalization - the ability to infer others' beliefs and intentions to guide one's own choices - is a key cognitive function underlying human social int

Benchmarking Clinical Decision Pathway Adherence in Large Language Models

arXiv:2608.26592v1 Announce Type: new Abstract: Following clinical decision pathways (CDPs) defined by clinical practice guidelines is essential for safe and reliable medical decision-making. However,

Beyond Accuracy: A Qualitative Analysis of Vision-Language Models for Hate Speech Detection in Memes

arXiv:2608.26143v1 Announce Type: cross Abstract: Memes have turned out to be a powerful tool through which individuals share their ideas concerning contemporary social and political problems. Their a

Beyond Factual QA: Mentorship-Oriented Question Answering over Long-Form Multilingual Content

arXiv:2601.17173v2 Announce Type: replace-cross Abstract: Question answering systems are typically evaluated on factual correctness, yet many real-world applications-such as education and career guida

CARE: Causally-Aligned Reasoning Exploration for Medical Large Language Models

arXiv:2608.26147v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for medical reasoning, yet the scarcity and cost of expert-annotated data constrain their progr