163 citations · 539 across the 205 of their papers we have counts for
220 papers
The Bottleneck Is Retrieval, Not Reading: Diagnosing Evidence-Based Generation with RAG for Long Context Question Answering
Debopriyo Banerjee, Owais Aijaz, Ahmer Tabassum +3
Retrieval-augmented generation (RAG) is the dominant paradigm for grounding large language models in external corpora, but its similarity-driven, chunked pipeline has structural bl…
MIC: Explaining Image-Claim Inconsistencies in AI-Generated Multimodal Misinformation
Ruihong Zeng, Jonathan Tonglet, Preslav Nakov +1
Claims paired with AI-generated images are a rapidly growing form of misinformation. Existing automated fact-checking (AFC) methods mainly treat this as a provenance problem, detec…
Same Scores, Different Decisions: Evaluating JEV and Language Models for Legal Document Understanding
Fan Zhang, Yankai Chen, Zhuohan Xie +11
Aggregate accuracy summarizes how often a model is correct, but not which judgments remain correct when requests change. We evaluate Jev and nine language models on ContractNLI, wi…
MedSNIP: Building and Benchmarking Snippet-Level Granularity for Medical Fact Verification
Hasan Iqbal, Sarfraz Ahmad, Hyunjae Kim +5
A medical claim's correctness often depends not on the claim alone, but on the clinical structure around it. A claim may require a lab reference range, a causal or conditional link…
FinCUABuild: Can Agents Build Reliable Benchmarks for Dynamic Financial Computer Use?
Jingpu Yang, Fengxian Ji, Jinri Guo +7
Financial scenarios are diverse and complex, spanning varying data conditions, tool configurations, and workflows. Yet existing CUA, Computer-Using Agent, evaluation tasks remain l…
How Correct Is Your Answer? A Semantic Correctness Framework for Open QA Evaluation
Elitsa Yotkova, Violeta Kastreva, Petar Velkov +4
Reliable evaluation of open-ended question answering remains a bottleneck for measuring answer correctness of modern LLMs. Unlike multiple-choice tasks, free-form answers may be co…
EDRAC: Benchmarking Arabic Dialect Reading Comprehension
Noor Abo Mokh, Kirill Chirkunov, Teresa Lynn +15
Dialectal Arabic (DA) remains under-resourced compared to Modern Standard Arabic (MSA), particularly for machine reading comprehension (MRC) and question answering (QA). Existing A…
Right Frame, Wrong Rule: Cultural Cues Expose the Financial Knowledge Gap They Were Meant to Close
Rania Elbadry, Ahmed Heakl, Saeed Almheiri +12
When a question has valid answers under different normative frameworks, a language model must decide which framework to use and whether it can answer correctly within it. We call t…
Can Agentic Trading Systems Pay for Their Own Intelligence?
Qiqi Duan, Changlun Li, Chen Wang +10
Large language model (LLM) agents are increasingly used in trading systems, where model reasoning, tool use, and continual decisions incur costs that are expected to produce tradin…
Think with Structured Grounding: Perceptual Reinforcement Learning for Chart and Visual-Tabular Understanding
Changjiang Jiang, Qiannian Zhao, Lei Xin +3
Multimodal Large Language Models (MLLMs) capable of thinking with images often rely on external tools for fine-grained perception. However, this reliance introduces significant inf…
SurakshaEval: An Indic Safety Benchmark for Multilingual LLMs
Debopriyo Banerjee, Kapil Rajesh Kavitha, Angana Borah +11
Existing safety evaluation datasets for large language models (LLMs) predominantly focus on English and Western contexts, often overlooking the linguistic diversity and culturally…
Seeing Is Not Deciding: Can Multimodal LLMs Act as Effective CEOs?
Yuyang Dai, Xueqing Peng, Yuxia Wang +2
Large language models are increasingly applied as autonomous decision-making agents. However, in executive business decisions, existing benchmarks are limited to textonly settings.…
LabGuard: Grounding Natural-Language Laboratory Rules into Runtime Guards for Embodied Laboratory Agents
Jingpu Yang, Fengxian Ji, Zhengzhao Lai +8
Scientific embodied agents are increasingly capable of carrying out laboratory procedures, but executing these procedures safely in dynamic laboratory environments remains challeng…
One More Turn, Less Regret: A Regret-Based Multi-Turn Benchmark for LLMs' Clarification Policies
Minh Ngoc Ta, My Anh Tran Nguyen, Duong D. Nguyen +2
Ambiguous user requests make clarification a sequential decision problem for conversational LLM assistants: they must decide whether to ask, what to ask, when to stop, and when to…
Overview of FinMMEval 2026 Task 2: Multilingual Financial Short-Answer Question Answering
Zhuohan Xie, Xueqing Peng, Georgi Georgiev +18
FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence. Each final-test item pairs an English question with financial statements and n…
Overview of FinMMEval 2026 Task 1: Multilingual Financial Multiple-Choice Question Answering
Zhuohan Xie, Yuyang Dai, Rania Elbadry +18
FinMMEval 2026 Task 1 evaluates multilingual financial multiple-choice question answering in English, Chinese, Arabic, and Hindi. The task tests whether systems can select the corr…
Trust Before Fusion: QIMG-7 and Source-Aware Resolution for Polluted Multimodal RAG
Saadeldine Eletter, Owais Aijaz, Preslav Nakov
Multimodal retrieval-augmented generation (RAG) is often evaluated with clean evidence, yet real retrieval can return topically relevant but unreliable content: false text and misl…
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
Jais 2: A Family of Arabic-Centric Open Large Language Models
Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim +57
Jais 2 is a family of Arabic-centric large language models developed jointly by MBZUAI, Cerebras, and Inception, designed to advance Arabic-centric language modeling, with strong p…
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution
Saadeldine Eletter, Ruihong Zeng, Yuxia Wang +3
Retrieval-Augmented Generation (RAG) improves factuality by grounding LLMs in external evidence, but real-world retrieval is often polluted: semantically relevant passages may cont…
Can Dialects Be Steered Like Languages? Sparse Neurons and Distributed Directions in Arabic LLMs
Kareem Elozeiri, Mervat Abassy, Omar Kallas +4
Dialectal data are scarce relative to Modern Standard Arabic (MSA), causing Arabic LLMs to overproduce MSA and struggle with dialectally accurate generation. This raises a fundamen…
FinPersona-Bench: A Benchmark for Longitudinal Psychometric Stability of Autonomous Financial Agents
Muhammad Usman Safder, Ayesha Gull, Rania Elbadry +7
Large Language Models (LLMs) are increasingly deployed as autonomous financial agents initialized with explicit behavioral mandates such as "preserve capital" or "avoid speculative…
CLExEval: A Human-in-the-Loop Framework for Qualitative Evaluation of LLM Clinical Reasoning
Ajmal M., Abin Roy, Afthab Salam Kanniyan +4
Large Language Models (LLMs) achieve strong results on many medical benchmarks, but their clinical reasoning remains difficult to evaluate reliably. A central risk is an evaluation…
The FIL Hypothesis: Inductive Biases Help with Kernel Engineering
Nikolai Rozanov, Subhabrata Dutta, Preslav Nakov +1
The Bitter Lesson, which posits that general-purpose methods that scale with computation and data ultimately outperform those with built-in human knowledge, has become a dominant p…