Lightnews — Scholar-powered news

Reposted by ERCbravenewword

Marco Ciapparelli @marcociapparelli.bsky.social · Jul 18

I'm sharing a Colab notebook on using large language models for cognitive science! GitHub repo: github.com/MarcoCiappar...

It's geared toward psychologists & linguists and covers extracting embeddings, predictability measures, comparing models across languages & modalities (vision). see examples 🧵

1 4 9

Reposted by ERCbravenewword

Gemma Boleda @gboleda.bsky.social · 8d

New paper! 🚨 I argue that LLMs represent a synthesis between distributed and symbolic approaches to language, because, when exposed to language, they develop highly symbolic representations and processing mechanisms in addition to distributed ones.
arxiv.org/abs/2502.11856

Sigmoid function. Non-linearities in neural network allow it to behave in distributed and near-symbolic fashions.

1 11 26

Reposted by ERCbravenewword

Giosuè Baggio @giosuebaggio.bsky.social · 12d

Important fMRI/RSA study by @marcociapparelli.bsky.social et al. Compositional (multiplicative) representations of compounds/phrases in left IFG (BA45), mSTS, ATL; left AG encodes constituents, not their composition, weighing the right element more, vice versa IFG 🧠🧩
academic.oup.com/cercor/artic...

Compositionality in the semantic network: a model-driven representational similarity analysis

Abstract. Semantic composition allows us to construct complex meanings (e.g., “dog house”, “house dog”) from simpler constituents (“dog”, “house”). Neuroim

academic.oup.com

4 9

ERCbravenewword @ercbravenewword.bsky.social · 13d

Great week at #ESLP2025 in Aix-en-Provence! Huge congrats to our colleagues for their excellent talks on computational models, sound symbolism, and multimodal cognition. Proud of the team and the stimulating discussions!

2 4

Reposted by ERCbravenewword

Caterina Villani @caterinavillani.bsky.social · 20d

📣The chapter "𝗦𝗽𝗲𝗰𝗶𝗳𝗶𝗰𝗶𝘁𝘆: 𝗠𝗲𝘁𝗿𝗶𝗰 𝗮𝗻𝗱 𝗡𝗼𝗿𝗺𝘀"
w/@mariannabolog.bsky.social is now online & forthcoming in the #ElsevierEncyclopedia of Language & Linguistics
🔍 Theoretical overview, quantification tools, and behavioral evidence on specificity.
👉 Read: urly.it/31c4nm
@abstractionerc.bsky.social

1 4 5

Reposted by ERCbravenewword

Valentina Pescuma @valentinapescuma.bsky.social · Aug 22

The dataset includes over 240K fixations and 150K word-level metrics, with saccade, fixation, and (word) interest area reports. Preprint osf.io/preprints/os..., data osf.io/hx2sj/. Work conducted with @davidecrepaldi.bsky.social and Maria Ktori. (2/2)

OSF

osf.io

1 1

Reposted by ERCbravenewword

Dirk Wulff @dirkwulff.bsky.social · Mar 11

How can we reduce conceptual clutter in the psychological sciences?

@ruimata.bsky.social and I propose a solution based on a fine-tuned 🤖 LLM (bit.ly/mpnet-pers) and test it for 🎭 personality psychology.

The paper is finally out in @natrevpsych.bsky.social: go.nature.com/4bEaaja

1 29 52

ERCbravenewword @ercbravenewword.bsky.social · 26d

For those who couldn't attend, the recording of Abhilasha Kumar's seminar on exploring form-meaning interactions in novel word learning and memory search is now available on our YouTube channel!!

Watch the full presentation here:
www.youtube.com/watch?v=VJTs...

Abhilasha Kumar, Beyond Arbitrariness: How a Word's Shape Influences Learning and Memory

YouTube video by Mbs Vector Space Lab

www.youtube.com

1 4

Reposted by ERCbravenewword

Marco Ciapparelli @marcociapparelli.bsky.social · 26d

Happy to share that our work on semantic composition is out now -- open access -- in Cerebral Cortex!

With Marco Marelli (@ercbravenewword.bsky.social), @wwgraves.bsky.social & @carloreve.bsky.social.

doi.org/10.1093/cerc...

3 11

ERCbravenewword @ercbravenewword.bsky.social · 29d

Great presentation by @fabiomarson.bsky.social last Saturday at #AMLAP2025! He shared his latest research using EEG to study how we integrate novel semantic representations, “linguistic chimeras”, from context.

Congratulations on a fascinating talk!

1 4

ERCbravenewword @ercbravenewword.bsky.social · 29d

For those who couldn't attend, the recording of Prof. Harald Baayen's seminar on morphological productivity and the Discriminative Lexicon Model is now available on our YouTube channel.

Watch the full presentation here:
www.youtube.com/watch?v=zN7G...

The Computational Approach to Morphological Productivity | Harald Baayen at Bicocca

YouTube video by Mbs Vector Space Lab

www.youtube.com

2 8

ERCbravenewword @ercbravenewword.bsky.social · Aug 27

New seminar announcement!

Exploring form-meaning interactions in novel word learning and memory search
Abhilasha Kumar (Assistant Professor, Bowdoin College)

A fantastic opportunity to delve into how we learn new words and retrieve them from memory.

💻 Join remotely: meet.google.com/pay-qcpv-sbf

ERCbravenewword @ercbravenewword.bsky.social · Aug 25

📢 Upcoming Seminar!

A computational approach to morphological productivity using the Discriminative Lexicon Model
Professor Harald Baayen (University of Tübingen, Germany)

🗓️ September 8, 2025
2:00 PM - 3:30 PM
📍 UniMiB, Room U6-01C, Milan
🔗 Join remotely: meet.google.com/dkj-kzmw-vzt

3 4

Reposted by ERCbravenewword

Qihong (Q) Lu @qlu.bsky.social · May 26

I’d like to share some slides and code for a “Memory Model 101 workshop” I gave recently, which has some minimal examples to illustrate the Rumelhart network & catastrophic interference :)
slides: shorturl.at/q2iKq
code (with colab support!): github.com/qihongl/demo...

hidden state representation during training

1 10 31

ERCbravenewword @ercbravenewword.bsky.social · Jul 8

🎉We're thrilled to welcome Jing Chen, PhD to our team!
She investigates how meanings are encoded and evolve, combining linguistic and computational approaches.
Her work spans diachronic modeling of lexical change in Mandarin and semantic transparency in LLMs.
🔗 research.polyu.edu.hk/en/publicati...

ChiWUG: A Graph-based Evaluation Dataset for Chinese Lexical Semantic Change Detection

research.polyu.edu.hk

1

ERCbravenewword @ercbravenewword.bsky.social · Jul 4

📢 New paper out! We show that auditory iconicity is not marginal in English: word sounds often resemble real-world sounds. Using neural networks and sound similarity measures, we crack the myth of arbitrariness.
Read more: link.springer.com/article/10.3...

@andreadevarda.bsky.social

Cracking arbitrariness: A data-driven study of auditory iconicity in spoken English - Psychonomic Bulletin & Review

Auditory iconic words display a phonological profile that imitates their referents’ sounds. Traditionally, those words are thought to constitute a minor portion of the auditory lexicon. In this articl...

link.springer.com

1 4

Reposted by ERCbravenewword

Marco Ciapparelli @marcociapparelli.bsky.social · Mar 19

1/n Happy to share a new paper with Calogero Zarbo & Marco Marelli! How well do LLMs represent the implicit meaning of familiar and novel compounds? How do they compare with simpler distributional semantics models (DSMs; i.e., word embeddings)?
doi.org/10.1111/cogs...

Conceptual Combination in Large Language Models: Uncovering Implicit Relational Interpretations in Compound Words With Contextualized Word Embeddings

Large language models (LLMs) have been proposed as candidate models of human semantics, and as such, they must be able to account for conceptual combination. This work explores the ability of two LLM...

doi.org

1 4 13

ERCbravenewword @ercbravenewword.bsky.social · Mar 18

Here's the video of the seminar for those who missed it. Enjoy!

youtu.be/p2YXb6WHCi4

Words are weird? On the role of lexical ambiguity in language - Gemma Boleda - unimib

YouTube video by Mbs Vector Space Lab

youtu.be

2

Reposted by ERCbravenewword

Cheng-Yu Hsieh @cyhsieh.bsky.social · Mar 10

1st post here! Excited to share this work with Marelli & @kathyrastle.bsky.social. We've found readers "routinely" combine constituent meanings for Chinese compound meaning, despite variability in constituent meaning and word structure, even when they're not asked to. See threads👇 for more details:

Compositional processing in the recognition of Chinese compounds: Behavioural and computational studies - Psychonomic Bulletin & Review

Recent research has shown that the compositional meaning of a compound is routinely constructed by combining meanings of constituents. However, this body of research has focused primarily on Germanic ...

doi.org

2 4 7

ERCbravenewword @ercbravenewword.bsky.social · Mar 3

Link to the seminar: meet.google.com/vwm-hsug-niv
📅 Don’t miss it!

meet.google.com

ERCbravenewword @ercbravenewword.bsky.social · Mar 3

📢 Upcoming Seminar

Words are weird? On the role of lexical ambiguity in language
🗣 Gemma Boleda (Universitat Pompeu Fabra, Spain)
Why is language so ambiguous? Discover how ambiguity balances cognitive simplicity and communicative complexity through large-scale studies.
📍 UniMiB, Room U6-01C, Milan

2 6 13

ERCbravenewword @ercbravenewword.bsky.social · Mar 3

⚠️ New Study Alert ⚠️

Humans can falsely recognize meaningless pseudowords when they resemble studied words. 🧠✨ This research shows that our brains detect hidden patterns, even without prior knowledge, leading to false memories.

🔗 Read more:
www.researchgate.net/publication/...

(PDF) False memories from nowhere: humans falsely recognize words that are not attested in their vocabulary

PDF | Semantic knowledge plays an active role in many well-known false memory phenomena, including those emerging from the Deese–Roediger–McDermott... | Find, read and cite all the research you need o...

www.researchgate.net

2

ERCbravenewword @ercbravenewword.bsky.social · Feb 18

📢 Upcoming Seminar
The Power of Words: The contribution of co-occurrence regularities of word use to the development of semantic organization
🗣 Olivera Savic (BCBL)
How do children grasp deeper word connections beyond simple meanings? Discover how word co-occurrence shapes semantic development

1 3

Reposted by ERCbravenewword

Proceedings of the National Academy of Sciences @pnas.org · Feb 11

One of the most-viewed PNAS articles in the last week is “Is Ockham’s razor losing its edge? New perspectives on the principle of model parsimony.” Explore the article here: www.pnas.org/doi/10.1073/...

For more trending articles, visit ow.ly/Me2U50SkLRZ.

Double descent of prediction error. Degree-one, degree-three, degree-twenty, and degree-one-thousand polynomial regression fits (magenta; from Left to Right) to data generated from a degree-three polynomial function (green). Low prediction error is achieved by both degree-three and degree-one-thousand models.

3 15

ERCbravenewword @ercbravenewword.bsky.social · Jan 25

Our @RBonandrini was bestowed a "Giovani talenti" award for his studies on word processing.

Congrats Rolando for this achievement! https://x.com/unimib/status/1870046485947265302

1