activity
20162026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 2.5k across the 94 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.CL2025

Structured RAG for Answering Aggregative Questions

Omri Koshorek, Niv Granot, Aviv Alloni +6

Retrieval-Augmented Generation (RAG) has become the dominant approach for answering questions over large corpora. However, current datasets and methods are highly focused on cases…

cs.CL2025

Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs

Itay Itzhak, Yonatan Belinkov, Gabriel Stanovsky

Large language models (LLMs) exhibit cognitive biases -- systematic tendencies of irrational decision-making, similar to those seen in humans. Prior work has found that these biase…

cs.IR2025

Reverse-Engineering the Retrieval Process in GenIR Models

Anja Reusch, Yonatan Belinkov

Generative Information Retrieval (GenIR) is a novel paradigm in which a transformer encoder-decoder model predicts document rankings based on a query in an end-to-end fashion. Thes…

cs.CL2025

Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models

Michael Toker, Ido Galil, Hadas Orgad +4

Text-to-image (T2I) diffusion models rely on encoded prompts to guide the image generation process. Typically, these prompts are extended to a fixed length by adding padding tokens…

cs.CL2025

Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models

Zeping Yu, Yonatan Belinkov, Sophia Ananiadou

We investigate how large language models perform latent multi-hop reasoning in prompts like "Wolfgang Amadeus Mozart's mother's spouse is". To analyze this process, we introduce lo…

cs.CL2025

Unsupervised Translation of Emergent Communication

Ido Levy, Orr Paradise, Boaz Carmeli +3

Emergent Communication (EC) provides a unique window into the language systems that emerge autonomously when agents are trained to jointly achieve shared goals. However, it is diff…

cs.LG2025

Position-aware Automatic Circuit Discovery

Tal Haklay, Hadas Orgad, David Bau +2

A widely used strategy to discover and understand language model mechanisms is circuit analysis. A circuit is a minimal subgraph of a model's computation graph that executes a spec…

cs.CL2025★ 2 cited

Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer

Adi Simhi, Itay Itzhak, Fazl Barez +2

Prior work on large language model (LLM) hallucinations has associated them with model uncertainty or inaccurate knowledge. In this work, we define and investigate a distinct type…