activity
20182026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 1.3k across the 96 of their papers we have counts for

collaborators

104 papers

cs.CL2026

DIAL-SUMMER: A Structured Evaluation Framework of Hierarchical Errors in Dialogue Summaries

Sahana Ramnath, Nima Chitsazan, Mingyang Zhou +8

Dialogues are a predominant mode of communication for humans, and it is immensely helpful to have automatically generated summaries of them (e.g., to revise key points discussed in…

cs.CL2026

Macaron: Controlled, Human-Written Benchmark for Multilingual and Multicultural Reasoning via Template-Filling

Alaa Elsetohy, Sama Hadhoud, Haryo Akbarianto Wibowo +4

Multilingual benchmarks rarely test reasoning over culturally grounded premises: translated datasets keep English-centric scenarios, while culture-first datasets often lack control…

cs.CL2026

PingPong: A Natural Benchmark for Multi-Turn Code-Switching Dialogues

Mohammad Rifqi Farhansyah, Hanif Muhammad Zhafran, Farid Adilazuarda +6

Code-switching is a widespread practice among the world's multilingual majority, yet few benchmarks accurately reflect its complexity in everyday communication. We present PingPong…

cs.CL2026

Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert Selection

Tianyi Niu, Justin Chih-Yao Chen, Genta Indra Winata +6

Large Language Model (LLM) routers dynamically select optimal models for given inputs. Existing approaches typically assume access to ground-truth labeled data, which is often unav…

cs.CL2026

CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data

Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94

Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…

cs.CV2025

Vision Language Models are Confused Tourists

Patrick Amadeus Irawan, Ikhlasul Akmal Hanif, Muhammad Dehan Al Kautsar +3

Although the cultural dimension has been one of the key aspects in evaluating Vision-Language Models (VLMs), their ability to remain stable across diverse cultural inputs remains l…

cs.CL2025

Leveraging Parameter Space Symmetries for Reasoning Skill Transfer in LLMs

Stefan Horoi, Sangwoo Cho, Supriyo Chakraborty +4

Task arithmetic is a powerful technique for transferring skills between Large Language Models (LLMs), but it often suffers from negative interference when models have diverged duri…

cs.LG2025

Optimizing Reasoning Efficiency through Prompt Difficulty Prediction

Bo Zhao, Berkcan Kapusuzoglu, Kartik Balasubramaniam +3

Reasoning language models perform well on complex tasks but are costly to deploy due to their size and long reasoning traces. We propose a routing approach that assigns each proble…

cs.CL2025

Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377

To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…

cs.CL2025

Entropy2Vec: Crosslingual Language Modeling Entropy as End-to-End Learnable Language Representations

Patrick Amadeus Irawan, Ryandito Diandaru, Belati Jagad Bintang Syuhada +5

We introduce Entropy2Vec, a novel framework for deriving cross-lingual language representations by leveraging the entropy of monolingual language models. Unlike traditional typolog…

cs.CL2025

SEADialogues: A Multilingual Culturally Grounded Multi-turn Dialogue Dataset on Southeast Asian Languages

Muhammad Dehan Al Kautsar, Aswin Candra, Muhammad Alif Al Hakim +6

Although numerous datasets have been developed to support dialogue systems, most existing chit-chat datasets overlook the cultural nuances inherent in natural human conversations.…

cs.CL2025

IndoPref: A Multi-Domain Pairwise Preference Dataset for Indonesian

Vanessa Rebecca Wiyono, David Anugraha, Ayu Purwarianti +1

Over 200 million people speak Indonesian, yet the language remains significantly underrepresented in preference-based research for large language models (LLMs). Most existing multi…

cs.CL2025

Language Surgery in Multilingual Large Language Models

Joanito Agili Lopo, Muhammad Ravi Shulthan Habibi, Tack Hwa Wong +6

Large Language Models (LLMs) have demonstrated remarkable generalization capabilities across tasks and languages, revolutionizing natural language processing. This paper investigat…

cs.CV2025

Behind Maya: Building a Multilingual Vision Language Model

Nahid Alam, Karthik Reddy Kanjula, Surya Guthikonda +16

In recent times, we have seen a rapid development of large Vision-Language Models (VLMs). They have shown impressive results on academic benchmarks, primarily in widely spoken lang…

cs.CL2025

T1: A Tool-Oriented Conversational Dataset for Multi-Turn Agentic Planning

Amartya Chakraborty, Paresh Dashore, Nadia Bathaee +6

Large Language Models (LLMs) have demonstrated impressive capabilities as intelligent agents capable of solving complex problems. However, effective planning in scenarios involving…

cs.CL2025★ 1 cited

R3: Robust Rubric-Agnostic Reward Models

David Anugraha, Zilu Tang, Lester James V. Miranda +5

Reward models are essential for aligning language model outputs with human preferences, yet existing approaches often lack both controllability and interpretability. These models a…

cs.CL2025

What Causes Knowledge Loss in Multilingual Language Models?

Maria Khelli, Samuel Cahyawijaya, Ayu Purwarianti +1

Cross-lingual transfer in natural language processing (NLP) models enhances multilingual performance by leveraging shared linguistic knowledge. However, traditional methods that pr…

cs.CV2025

Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia

Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz +89

Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often resu…

cs.LG2025

RPO: Fine-Tuning Visual Generative Models via Rich Vision-Language Preferences

Hanyang Zhao, Haoxian Chen, Yucheng Guo +5

Traditional preference tuning methods for LLMs/Visual Generative Models often rely solely on reward model labeling, which can be opaque, offer limited insights into the rationale b…

cs.CL2025

TextGames: Learning to Self-Play Text-Based Puzzle Games via Language Model Reasoning

Frederikus Hudi, Genta Indra Winata, Ruochen Zhang +1

Reasoning is a fundamental capability of large language models (LLMs), enabling them to comprehend, analyze, and solve complex problems. In this paper, we introduce TextGames, an i…

cs.CL2025

Do Language Models Understand Honorific Systems in Javanese?

Mohammad Rifqi Farhansyah, Iwan Darmawan, Adryan Kusumawardhana +3

The Javanese language features a complex system of honorifics that vary according to the social status of the speaker, listener, and referent. Despite its cultural and linguistic s…

cs.CL2025★ 15 cited

MMTEB: Massive Multilingual Text Embedding Benchmark

Kenneth Enevoldsen, Isaac Chung, Imene Kerboua +83

Text embeddings are typically evaluated on a limited set of tasks, which are constrained by language, domain, and task diversity. To address these limitations and provide a more co…

cs.CV2024

Maya: An Instruction Finetuned Multilingual Multimodal Model

Nahid Alam, Karthik Reddy Kanjula, Surya Guthikonda +16

The rapid development of large Vision-Language Models (VLMs) has led to impressive results on academic benchmarks, primarily in widely spoken languages. However, significant gaps r…

cs.HC2024★ 2 cited

A Multi-Agent Dual Dialogue System to Support Mental Health Care Providers

Onno P. Kampman, Ye Sheng Phang, Stanley Han +9

We introduce a general-purpose, human-in-the-loop dual dialogue system to support mental health care professionals. The system, co-designed with care providers, is conceptualized t…